Notes

• This notebook has implementations of Backprop with binary spike feature vectors obtained from the SPIKEFLOW. Here, we will use tf.data API. Here the shape of the inputs is [None, n_input] instead of [n_input, None]. We had to do this because nested elements in from_tensor_slices must have the same dimension in 0th rank see. Everytime an iterator iter = dataset.make_initializable_iterator() gets initialized, the dataset is randomly shuffled so we need not shuffle again, see. We also use z_3 = tf.floor(z_3). Surrogate gradients with one step is used. (one sided)

• Here, error in the hidden layer, $\delta^{2}$ is implemented as: $ \delta^{2} = W^{3T}\delta^{(3)}\odot\sigma^{'}(z^{(2)}) \tag{1}$

• $\sigma^{'}(z^{(2)})$ is approximated with a surrogate. (See section 6)
• It also takes care of catastrophic forgetting by using synaptic intelligence.
• He initialization without AR1 gives lesser final accuracy than Trunc init because in He the gradients don't suffer from dimnishing. ### References
• Neural Nets
• Randombackprop
• Randombackprop
• Backprop
• Initializers
• Dropout
• Softmax
• SoftmaxLogits
• TF memory leaks when assigning in loop

import os, time
#os.environ["CUDA_VISIBLE_DEVICES"]="-1"
import matplotlib.pyplot as plt
import matplotlib as mpl
import tensorflow as tf
from IPython.display import display, HTML
tf.compat.v2.random.set_seed(0)
from tensorflow.examples.tutorials.mnist import input_data
from tensorflow.python.client import timeline
import h5py, pickle
from keras.utils.np_utils import to_categorical 
import numpy as np
import pandas as pd
import DATA_Loader
import seaborn as sb
import theano, random, sys, time

/usr/local/lib/python2.7/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
Using TensorFlow backend.

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
print(tf.__version__)
tf

1.14.0

<module 'tensorflow' from '/home/ruthvik/.local/lib/python2.7/site-packages/tensorflow/__init__.pyc'>

Hide code

HTML('''<script>
code_show=true; 
function code_toggle() {
if (code_show){
$('div.input').hide();
} else {
$('div.input').show();
}
code_show = !code_show
} 
$( document ).ready(code_toggle);
</script>
<form action="javascript:code_toggle()"><input type="submit" value="Click here to toggle on/off the raw code."></form>''')

Plots

• FOR PRETTY IEEE PLOTS mpl.rcParams['figure.figsize'] = 4.5,2.5, all fonts 9-12

Large

mpl.rcParams['figure.figsize'] = 15,10
mpl.rcParams['axes.titlesize'] = 24
mpl.rcParams['axes.labelsize'] = 25
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.markersize'] = 10
mpl.rcParams['xtick.labelsize'] = 30
mpl.rcParams['ytick.labelsize'] = 22
mpl.rcParams['legend.fontsize'] = 25
mpl.rcParams['font.size'] = 22

Small

plt.style.use('ggplot')
mpl.rcParams['figure.figsize'] = 3.75,3
mpl.rcParams['axes.titlesize'] = 12
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.markersize'] = 10
mpl.rcParams['xtick.labelsize'] = 12
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12
mpl.rcParams['font.size'] = 12

Load the data

filename = '../../spiking_networks/train_pool1_spike_features_inh_False_conv1maps_30.h5'
with h5py.File(filename, 'r') as hf:
    emnist_train_images = hf['pool1_spike_features'][:].astype(np.int8)
emnist_train_images[np.where(emnist_train_images>=1)] = 1

filehandle = open('../../spiking_networks/train_y.pkl','rb')
emnist_train_labels = pickle.load(filehandle).astype(np.int).tolist()
filehandle.close()
emnist_train_labels = np.array(emnist_train_labels)
print('Total train features:{}'.format(emnist_train_images.shape[0]))

#### LOAD TEST IMAGES AND LABELS
filename = '../../spiking_networks/test_pool1_spike_features_inh_False_conv1maps_30.h5'
with h5py.File(filename, 'r') as hf:
    emnist_test_images = hf['pool1_spike_features'][:].astype(np.int8)
emnist_test_images[np.where(emnist_test_images>=1)] = 1
print('Total test features:{}'.format(emnist_test_images.shape[0]))

filehandle = open('../../spiking_networks/test_y.pkl','rb')
emnist_test_labels = pickle.load(filehandle).astype(np.int)
filehandle.close()
emnist_test_labels = np.array(emnist_test_labels)

#### LOAD TRAIN AND VALIDATION DATA AND LABELS
train_images = emnist_train_images
train_labels = emnist_train_labels
train_labels = np.array(train_labels)
test_images = emnist_test_images
test_labels = emnist_test_labels
num_classes=10

Total train features:60000
Total test features:10000

labels_map = {0:'0',1:'1',2:'2',3:'3',4:'4',5:'5',6:'6',7:'7',8:'8',9:'9',10:'A',11:'B',12:'C',13:'D',14:'E',15:'F',
              16:'G',17:'H',18:'I',19:'J',20:'K',21:'L',22:'M',23:'N',24:'O',25:'P',26:'Q',27:'R',28:'S',29:'T',30:'U',
             31:'V',32:'W',33:'X',34:'Y',35:'Z',36:'a',37:'b',38:'d',39:'e',40:'f',41:'g',42:'h',43:'n',44:'q',45:'r',
             46:'t'}

BATCH_SIZE = 10
#### EXTRACT REQUIRED LOCATIONS OF 0 TO 5 FOR TRAIN DATA
def extract_class_data(start=0, stop=1):
    set1_locs = np.where((train_labels>=start) & (train_labels<=stop))[0]
    train_labels_set1 = to_categorical(train_labels[set1_locs], num_classes=num_classes)
    train_images_set1 = train_images[set1_locs,:]
    n_images = len(train_images_set1)

    #### EXTRACT REQUIRED LOCATIONS OF 0 TO 5 FOR TEST DATA
    set1_locs = np.where((test_labels>=start) & (test_labels<=stop))[0]
    test_labels_set1 = to_categorical(test_labels[set1_locs], num_classes=num_classes)
    test_images_set1 = test_images[set1_locs,:]
    print('Test features:{}'.format(test_images_set1.shape))
    print('Length of test labels:{}'.format(test_labels_set1.shape[0]))
    test_data_set1 = (test_images_set1, test_labels_set1)
    


    train_images_set1 = train_images_set1[int(0.09*n_images):]
    train_labels_set1 = train_labels_set1[int(0.09*n_images):]
    print('Train features:{}'.format(train_images_set1.shape))
    print('Length of train labels:{}'.format(train_labels_set1.shape[0]))
    train_data_set1 = (train_images_set1, train_labels_set1)

    valid_labels_set1 = train_labels_set1[0:int(0.09*n_images)]
    valid_images_set1 = train_images_set1[0:int(0.09*n_images)]
    print('Valid features:{}'.format(valid_images_set1.shape))
    print('Length of valid labels:{}'.format(valid_labels_set1.shape[0]))
    valid_data_set1 = (valid_images_set1, valid_labels_set1)
    
    n_train_set1 = train_labels_set1.shape[0]
    n_test_set1 = test_labels_set1.shape[0]
    n_valid_set1 = valid_labels_set1.shape[0]

    return train_data_set1, valid_data_set1, test_data_set1

Start a session

tf.reset_default_graph()
config = tf.ConfigProto()
config.gpu_options.allow_growth=True
sess= tf.InteractiveSession(config=config)
run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
run_metadata = tf.RunMetadata()

$tanh(x) = \frac{(e^{x} – e^{-x})}{(e^{x} + e^{-x})}$

$d\frac{tanh(x)}{dx} = 1 – (tanh(x))^{2}$

$\sigma(x) = \frac{1.0}{1 + e^{-x}}$

$d\frac{\sigma(x)}{dx} = \sigma(x)*(1 - \sigma(x))$

Setup the network graph

n_input = 3630
n_middle = 1024
n_out = 10
batch_size = tf.placeholder(tf.int64, name='batch_size') 
a_1 = tf.placeholder(tf.float32, [None, n_input], name = 'Input_batch')
y = tf.placeholder(tf.float32, [None, n_out], name = 'output_batch')
dataset = tf.data.Dataset.from_tensor_slices((a_1, y))
#dataset = dataset.shuffle(buffer_size=len(all_train_labels), reshuffle_each_iteration=True)
dataset = dataset.batch(batch_size)
iter = dataset.make_initializable_iterator()
features, labels = iter.get_next()

drop_out = tf.placeholder(tf.float32)
tau = tf.placeholder(tf.float32)
set1_mask = tf.placeholder(tf.float32, [10], name='mask')
eta = tf.placeholder(tf.float32)
n_tot = tf.placeholder(tf.float32)
lmbda = tf.placeholder(tf.float32, name='lambda')
with tf.name_scope('hid_lyr_w_b'):  ###havier or glorot initialization
    low = -4*tf.math.sqrt(6.0/(n_input + n_middle)) # use 4 for sigmoid, 1 for tanh activation 
    high = 4*tf.math.sqrt(6.0/(n_input + n_middle))
    
    low = -tf.math.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
    high = tf.math.sqrt(2.0/(n_input))
    
    w_2 = tf.Variable(tf.random_uniform(shape=[n_input,n_middle],minval=low,maxval=high), name = 'W_2')
    #w_2 = tf.Variable(tf.truncated_normal(shape=[n_input,n_middle], stddev=0.01),name = 'W_2')
    w_2_update_placeholder = tf.placeholder(w_2.dtype, shape=w_2.get_shape(),name='update_w2')
    w_2_update_op = w_2.assign(w_2_update_placeholder)
    tf.summary.histogram('w_2', w_2)
    
    b_2 = tf.Variable(tf.zeros([1,n_middle]), name = 'b_2')
    b_2_update_placeholder = tf.placeholder(b_2.dtype, shape=b_2.get_shape(),name='update_b2')
    b_2_update_op = b_2.assign(b_2_update_placeholder)
    tf.summary.histogram('b_2', b_2)
    
    
    w2_grad_accum = tf.Variable(np.zeros(shape=[n_input,n_middle], dtype=np.float32),name='w2_grad_accum')
    w2_grad_accum_update_placeholder=tf.placeholder(w2_grad_accum.dtype, shape=w2_grad_accum.get_shape(),
                                            name='update_w2_grad_accum')
    w2_grad_accum_update_op = w2_grad_accum.assign(w2_grad_accum_update_placeholder)
    
    
    b2_grad_accum = tf.Variable(np.zeros(shape=[1,n_middle], dtype=np.float32), name='b2_grad_accum')
    b2_grad_accum_update_placeholder=tf.placeholder(b2_grad_accum.dtype,shape=b2_grad_accum.get_shape(),
                                            name='update_b2_grad_accum')
    b2_grad_accum_update_op = b2_grad_accum.assign(b2_grad_accum_update_placeholder)
    
    
    big_omeg_w2 = tf.Variable(np.zeros(shape=[n_input,n_middle], dtype=np.float32), name='omeg_w2')
    tf.summary.histogram('big_omeg_w2', big_omeg_w2)
    big_omeg_w2_update_placeholder = tf.placeholder(big_omeg_w2.dtype, shape=big_omeg_w2.get_shape(),
                                                    name='update_big_omeg_w2')
    big_omeg_w2_update_op = big_omeg_w2.assign(big_omeg_w2_update_placeholder)
    
    
    big_omeg_b2 = tf.Variable(np.zeros(shape=[1,n_middle], dtype=np.float32), name='omeg_b2')
    tf.summary.histogram('big_omeg_b2', big_omeg_b2)
    big_omeg_b2_update_placeholder = tf.placeholder(big_omeg_b2.dtype, shape=big_omeg_b2.get_shape(),
                                                    name='update_big_omeg_b2')
    big_omeg_b2_update_op = big_omeg_b2.assign(big_omeg_b2_update_placeholder)
    
    
    star_w2 = tf.Variable(np.zeros(shape=[n_input,n_middle], dtype=np.float32), name='star_w2')
    star_w2_update_placeholder = tf.placeholder(star_w2.dtype, shape=star_w2.get_shape(),
                                                name='update_star_w2')
    star_w2_update_op = star_w2.assign(star_w2_update_placeholder)
    
    
    star_b2 = tf.Variable(np.zeros(shape=[1,n_middle], dtype=np.float32), name='star_b2')
    star_b2_update_placeholder = tf.placeholder(star_b2.dtype, shape=star_b2.get_shape(),
                                                name='update_star_b2')
    star_b2_update_op = star_b2.assign(star_b2_update_placeholder)
with tf.name_scope('op_lyr_w_b'):
    
    low = -tf.math.sqrt(2.0/(n_middle))
    high = tf.math.sqrt(2.0/(n_middle))
    #w_3 = tf.Variable(tf.random_uniform(shape=[n_middle,10],minval=low,maxval=high), name = 'W_3')
    #w_3 = tf.Variable(tf.truncated_normal(shape=[n_middle,n_out], stddev=0.01),name = 'W_3')
    w_3 = tf.Variable(np.zeros(shape=[n_middle,n_out], dtype=np.float32),name = 'W_3')
    tf.summary.histogram('w_3', w_3)
    w_3_update_placeholder = tf.placeholder(w_3.dtype, shape=w_3.get_shape(),name='update_w3')
    w_3_update_op = w_3.assign(w_3_update_placeholder)
    
    b_3 = tf.Variable(tf.zeros([1,n_out]), name = 'b_3')
    tf.summary.histogram('b_3', b_3)
    b_3_update_placeholder = tf.placeholder(b_3.dtype, shape=b_3.get_shape(),name='update_b3')
    b_3_update_op = b_3.assign(b_3_update_placeholder)
    
    w3_grad_accum = tf.Variable(np.zeros(shape=[n_middle,n_out], dtype=np.float32), name='w3_grad_accum')
    b3_grad_accum = tf.Variable(np.zeros(shape=[1,n_out], dtype=np.float32), name='b3_grad_accum')
    
    big_omeg_w3 = tf.Variable(np.zeros(shape=[n_middle,n_out], dtype=np.float32), name='omeg_w3')
    tf.summary.histogram('big_omeg_w3', big_omeg_w3)
    big_omeg_b3 = tf.Variable(np.zeros(shape=[1,n_out], dtype=np.float32), name='omeg_b3')
    tf.summary.histogram('big_omeg_b3', big_omeg_b3)
    
    star_w3 = tf.Variable(np.zeros(shape=[n_middle,n_out], dtype=np.float32), name='star_w3')
    star_b3 = tf.Variable(np.zeros(shape=[1,n_out], dtype=np.float32), name='star_b3')

def sigma(x):
    return tf.math.divide(tf.constant(1.0),
                  tf.add(tf.constant(1.0), tf.exp(tf.negative(x))))
def tanh(x):
    return tf.math.divide(tf.subtract(tf.exp(x), tf.exp(tf.negative(x))), 
                          tf.add(tf.exp(x), tf.exp(tf.negative(x))) )

def sigmaprime(x):
    return tf.multiply(sigma(x), tf.subtract(tf.constant(1.0), sigma(x)))

def tanhprime(x):
    return tf.subtract(tf.constant(1.0),tf.square(tanh(x)))

def spkNeuron(x):
    return tf.where(tf.greater_equal(x,0.0), tf.ones_like(x), 
                        tf.zeros_like(x))

def ReLU(x):
    return tf.maximum(0.0, x)

def ReLUprime(x):
    return tf.where(tf.greater_equal(x,0.0), tf.ones_like(x), 
                        tf.zeros_like(x))

def spkPrime1(x):
    l1_bound_higher = tf.greater_equal(x,-0/4)
    r1_bound_lesser = tf.less_equal(x,tau/4) 
    grad_one = tf.where(tf.logical_and(l1_bound_higher,r1_bound_lesser), tf.ones_like(x), tf.zeros_like(x))
    return grad_one

def firstLyrSpks(x):
    return tf.where(tf.greater_equal(x,1.0), tf.ones_like(x), 
                        tf.zeros_like(x))

    
with tf.name_scope('hid_lyr_acti'):
    z_2 = tf.add(tf.matmul(features,w_2,name = 'w_2xa_1'), b_2, name = 'z_2')
    locs_to_drop = tf.random.categorical(tf.math.log([[1.0-drop_out, drop_out]]), tf.size(z_2))
    locs_to_drop = tf.reshape(locs_to_drop, tf.shape(z_2))
    z_2 = tf.where(locs_to_drop>0,-tf.ones_like(z_2),z_2, 'drop_out_app')
    tf.summary.histogram('z_2', z_2)
    a_2 = ReLU(z_2)
    #@@a_2 = spkNeuron(z_2)
    tf.summary.histogram('a_2', a_2)
with tf.name_scope('op_lyr_acti'):
    z_3 = tf.add(tf.matmul(a_2,w_3, name = 'w_3xa_2'),b_3, name = 'z_3')
    z_3 = tf.floor(z_3)
    #z_3 = tf.subtract(tf.reduce_max(z_3),z_3, name = 'inhibition')
    tf.summary.histogram('z_3', z_3)
    a_3 = tf.cast(tf.nn.softmax(z_3,axis=1), tf.float32)
    a_3 = tf.multiply(a_3, set1_mask, name='masking')
    tf.summary.histogram('a_3', a_3)
    ##COMMENT THE ABOVE LINE AND UNCOMMENT BELOW LINE IF YOU WANT SOFTMAX
    #a_3 = tf.nn.softmax(z_3,axis=1) ##AXIS IS VERY IMPORTANT!!! axis=1 INDICATES THE CLASSES AS y IS [None,10]

#cost = tf.reduce_mean(-tf.reduce_sum((y*tf.log(a_3) +tf.log(1-a_3)*(1-y)) ,axis=0), name = 'cost_calc') WORKS, USE BELOW
with tf.name_scope('cost_calc'):
    cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(labels=labels,logits=z_3,axis=1),
                          name = 'cost_calc')#WORKS
        ##COMMENT BELOW LINES IF YOU WANT quadratic
    #@dc_da = tf.multiply(-tf.subtract(labels,a_3, name = 'y_minus_a_3'), mask)
    #@cost = tf.reduce_mean(tf.reduce_sum((1/2.0)*tf.square(dc_da),axis=1), name = 'cost_calc')
    tf.summary.scalar('cost', cost)

with tf.name_scope('op_lyr_grad'):
    #@d_z_3 = tf.multiply(-tf.subtract(labels,a_3, name = 'delta3'), mask, name='masking')
    d_z_3 = -tf.subtract(labels,a_3, name = 'delta3')
    #d_z_3 = tf.multiply(dc_da,a_3, name = 'delta3')
    d_b_3 = tf.expand_dims(tf.reduce_mean(d_z_3, axis=[0]), axis=0)
    tf.summary.histogram('d_b_3', d_b_3)
    d_w_3 = tf.multiply(1/tf.cast(batch_size, tf.float32),
                        tf.matmul(tf.transpose(a_2),d_z_3), 
                        name='delta_w3')
    tf.summary.histogram('d_w_3', d_w_3)
    
with tf.name_scope('hid_lyr_grad'):
    d_z_2 = tf.multiply(tf.matmul(d_z_3,tf.transpose(w_3), name = 'w_3Txdelta3'), ReLUprime(z_2),
                        name = 'delta2')
    #@@d_z_2 = tf.multiply(tf.matmul(d_z_3,tf.transpose(w_3), name = 'w_3Txdelta3'), spkPrime1(z_2),
    #@@                    name = 'delta2')
    #d_z_2 = tf.matmul(d_z_3,tf.transpose(w_3), name = 'delta2')
    d_b_2 = tf.expand_dims(tf.reduce_mean(d_z_2, axis=[0]), axis=0)
    tf.summary.histogram('d_b_2', d_b_2)
    d_w_2 = tf.multiply(1/tf.cast(batch_size, tf.float32),
                        tf.matmul(tf.transpose(features),d_z_2), 
                        name='delta_w2')
    tf.summary.histogram('d_w_2', d_w_2)
    
omega_step=[tf.assign(w2_grad_accum,
                      tf.add(w2_grad_accum,tf.multiply(eta*eta*lmbda/n_tot, tf.square(d_w_2))),
                     name='update_omeg_w2'),
            tf.assign(b2_grad_accum,
                      tf.add(b2_grad_accum,tf.multiply(eta*eta*lmbda/n_tot,tf.square(d_b_2))),
                     name='update_omeg_b2')
]

step = [tf.assign(w_2,
                  tf.subtract(w_2, (eta*d_w_2+big_omeg_w2*(w_2-star_w2))),name='update_w_2'),
        tf.assign(b_2,
                  tf.subtract(b_2,(eta*d_b_2+big_omeg_b2*(b_2-star_b2))),name='update_b_2'),
        
        tf.assign(w_3,
                  tf.subtract(w_3, (eta*d_w_3+big_omeg_w3*(w_3-star_w3))),name='update_w_3'),
        tf.assign(b_3,
                  tf.subtract(b_3,(eta*d_b_3+big_omeg_b3*(b_3-star_b3))),name='update_b_3')    
]
with tf.name_scope('acc_calc'):
    predictions = tf.argmax(a_3, 1)
    acct_mat = tf.equal(tf.argmax(a_3, 1), tf.argmax(labels, 1))
    acct_res = tf.reduce_mean(tf.cast(acct_mat, tf.float32))
    tf.summary.scalar('accuracy', acct_res)

init_op = tf.global_variables_initializer()

Init the writer with $\lambda$s (0, 6.75)e4

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_16lmbdas_ar1_3lyrs_he1', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 15
a = np.random.uniform(low=0.0, high=6.75, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 5
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[3.66798336 1.87899335 2.86549374 5.70223889 0.03185228 0.82059157
 4.52755632 5.5745061  0.92276948 3.88187997 6.01642319 1.41211432
 1.25096548 0.73154401 1.48295808]
()
[  318.52279289  7315.44010634  8205.91565286  9227.69480373
 12509.65481963 14121.14324291 14829.58075219 18789.93349383
 28654.93737557 36679.83357089 38818.79973634 45275.56321906
 55745.06096959 57022.38893159 60164.23191608]
()
([0, 318.52279289064813, 7315.4401063372225, 8205.915652860209, 9227.694803734325, 12509.654819630066, 14121.143242910297, 14829.58075218697, 18789.933493831242, 28654.937375566486, 36679.833570890165, 38818.79973633937, 45275.563219057556, 55745.06096959071, 57022.388931593494, 60164.23191607782, 0, 318.52279289064813, 7315.4401063372225, 8205.915652860209, 9227.694803734325, 12509.654819630066, 14121.143242910297, 14829.58075218697, 18789.933493831242, 28654.937375566486, 36679.833570890165, 38818.79973633937, 45275.563219057556, 55745.06096959071, 57022.388931593494, 60164.23191607782, 0, 318.52279289064813, 7315.4401063372225, 8205.915652860209, 9227.694803734325, 12509.654819630066, 14121.143242910297, 14829.58075218697, 18789.933493831242, 28654.937375566486, 36679.833570890165, 38818.79973633937, 45275.563219057556, 55745.06096959071, 57022.388931593494, 60164.23191607782, 0, 318.52279289064813, 7315.4401063372225, 8205.915652860209, 9227.694803734325, 12509.654819630066, 14121.143242910297, 14829.58075218697, 18789.933493831242, 28654.937375566486, 36679.833570890165, 38818.79973633937, 45275.563219057556, 55745.06096959071, 57022.388931593494, 60164.23191607782, 0, 318.52279289064813, 7315.4401063372225, 8205.915652860209, 9227.694803734325, 12509.654819630066, 14121.143242910297, 14829.58075218697, 18789.933493831242, 28654.937375566486, 36679.833570890165, 38818.79973633937, 45275.563219057556, 55745.06096959071, 57022.388931593494, 60164.23191607782], 80)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(80, 80)

np.array_equal(np_weights[0], np_weights[15])

True

np.array_equal(np_weights[0], np_weights[16])

False

Commence training

method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:130.874908924
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:122.635829926
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990518555045 and training accuracy:0.991609752178
validation cost:0.0925189256668 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0539999529719 and training accuracy:0.99287801981
validation cost:0.0477138087153 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0376890674233 and training accuracy:0.994829297066
validation cost:0.0302194636315 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0290481522679 and training accuracy:0.99658536911
validation cost:0.0220831781626 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023657489568 and training accuracy:0.997756123543
validation cost:0.0176057368517 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198712404817 and training accuracy:0.998341441154
validation cost:0.0145276719704 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169922467321 and training accuracy:0.998341441154
validation cost:0.0122214574367 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0153050273657 and training accuracy:0.998146355152
validation cost:0.011213125661 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139560960233 and training accuracy:0.998243927956
validation cost:0.0100094126537 and validation accuracy:1.0
Training on :(4, 5)
Time taken:130.478960991
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636208951473 and training accuracy:0.991611778736
validation cost:0.0635736957192 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0342947021127 and training accuracy:0.996843159199
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:7315.44010634, 2
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8205.91565286, 3
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.412664175
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:14121.1432429, 22
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.786099970341
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.786800026894
Training with lmbda:7315.44010634, 34
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.314898014
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.786800026894
Training with lmbda:14829.5807522, 39
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:18789.9334938, 40
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.152856827
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:57022.3889316, 46
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Train features:(10738, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:60164.2319161, 47
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.796400010586
Training with lmbda:45275.5632191, 60
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.915061951
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:55745.0609696, 61
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.737991095
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:121.694267035
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:57022.3889316, 62
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:112.603735924
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:112.397829056
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.104044914
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Training with lmbda:9227.69480373, 68
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0442401729524 and training accuracy:0.986546695232
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Training on :(2, 3)
Time taken:120.567087889
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:121.524744034
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.535394192
Method 3 test accuracy:0.778299987316
Training with lmbda:12509.6548196, 69
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Valid features:(1088, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:121.834098101
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.636846066
Method 3 test accuracy:0.778199970722
Training with lmbda:14121.1432429, 70
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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validation cost:0.0419569499791 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:117.604227066
Method 3 test accuracy:0.778800010681

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_16lmbdas_ar1_3lyrs_he1.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7901	318.522793
2	0.7897	7315.440106
3	0.7877	8205.915653
4	0.7838	9227.694804
5	0.7834	12509.654820
6	0.7833	14121.143243
7	0.7825	14829.580752
8	0.7828	18789.933494
9	0.7815	28654.937376
10	0.7826	36679.833571
11	0.7835	38818.799736
12	0.7828	45275.563219
13	0.7808	55745.060970
14	0.7773	57022.388932
15	0.7806	60164.231916
16	0.7927	0.000000
17	0.7923	318.522793
18	0.7909	7315.440106
19	0.7919	8205.915653
20	0.7922	9227.694804
21	0.7915	12509.654820
22	0.7861	14121.143243
23	0.7918	14829.580752
24	0.7918	18789.933494
25	0.7923	28654.937376
26	0.7927	36679.833571
27	0.7866	38818.799736
28	0.7929	45275.563219
29	0.7922	55745.060970
...	...	...
50	0.7902	7315.440106
51	0.7897	8205.915653
52	0.7905	9227.694804
53	0.7905	12509.654820
54	0.7876	14121.143243
55	0.7867	14829.580752
56	0.7864	18789.933494
57	0.7981	28654.937376
58	0.7909	36679.833571
59	0.7964	38818.799736
60	0.7894	45275.563219
61	0.7851	55745.060970
62	0.8053	57022.388932
63	0.7904	60164.231916
64	0.7784	0.000000
65	0.7790	318.522793
66	0.7783	7315.440106
67	0.7790	8205.915653
68	0.7783	9227.694804
69	0.7782	12509.654820
70	0.7786	14121.143243
71	0.7780	14829.580752
72	0.7775	18789.933494
73	0.7776	28654.937376
74	0.7780	36679.833571
75	0.7785	38818.799736
76	0.7783	45275.563219
77	0.7786	55745.060970
78	0.7784	57022.388932
79	0.7788	60164.231916

80 rows × 2 columns

final_test_accuracies [0.682, 0.7121, 0.7243, 0.5746, 0.5998, 0.6755, 0.7068, 0.7382, 0.6611, 0.6537] for lmbdas = np.array([1.0+i/10.0 for i in range(1,11)])*1.0e5 lmbdas = lmbdas.tolist()

Groupby $\lambda$

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
mean_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
display(mean_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.78762
318.522793	0.78752
7315.440106	0.78726
8205.915653	0.78698
9227.694804	0.78634
12509.654820	0.78596
14121.143243	0.78448
14829.580752	0.78520
18789.933494	0.78504
28654.937376	0.78736
36679.833571	0.78618
38818.799736	0.78628
45275.563219	0.78608
55745.060970	0.78482
57022.388932	0.78820
60164.231916	0.78588

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
std_acc_grouped_by_lmbda = acc_grouped_by_lmbda.std()
display(std_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.005442
318.522793	0.005151
7315.440106	0.005199
8205.915653	0.004898
9227.694804	0.005546
12509.654820	0.005434
14121.143243	0.003664
14829.580752	0.005200
18789.933494	0.005296
28654.937376	0.008206
36679.833571	0.006016
38818.799736	0.006534
45275.563219	0.005694
55745.060970	0.005386
57022.388932	0.011505
60164.231916	0.005951

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
max_acc_grouped_by_lmbda = acc_grouped_by_lmbda.max()
display(max_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.7927
318.522793	0.7923
7315.440106	0.7909
8205.915653	0.7919
9227.694804	0.7922
12509.654820	0.7915
14121.143243	0.7876
14829.580752	0.7918
18789.933494	0.7918
28654.937376	0.7981
36679.833571	0.7927
38818.799736	0.7964
45275.563219	0.7929
55745.060970	0.7922
57022.388932	0.8053
60164.231916	0.7923

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

mean_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

Some histograms

W_2

plt.hist(w_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_W_2

plt.hist(new_big_omeg_w2.flatten(),bins=100,log=True)
#plt.yscale('log')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_2

plt.hist(b_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_b_2

plt.hist(new_big_omeg_b2.flatten(),100,log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

W_3

plt.hist(w_3.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_3

plt.hist(b_3.eval().flatten(), 10)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (0, 6.75*2.5)e4

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_16lmbdas_ar1_3lyrs_he1_v2', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 15
a = np.random.uniform(low=0.0, high=6.75, size=(n_lmbdas,))
print(a)
print()
a = a*2.5e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 5
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[3.66798336 1.87899335 2.86549374 5.70223889 0.03185228 0.82059157
 4.52755632 5.5745061  0.92276948 3.88187997 6.01642319 1.41211432
 1.25096548 0.73154401 1.48295808]
()
[   796.30698223  18288.60026584  20514.78913215  23069.23700934
  31274.13704908  35302.85810728  37073.95188047  46974.83373458
  71637.34343892  91699.58392723  97046.99934085 113188.90804764
 139362.65242398 142555.97232898 150410.57979019]
()
([0, 796.3069822266202, 18288.600265843055, 20514.789132150523, 23069.237009335815, 31274.13704907517, 35302.858107275744, 37073.95188046742, 46974.833734578104, 71637.34343891621, 91699.58392722541, 97046.99934084844, 113188.9080476439, 139362.65242397678, 142555.97232898374, 150410.57979019455, 0, 796.3069822266202, 18288.600265843055, 20514.789132150523, 23069.237009335815, 31274.13704907517, 35302.858107275744, 37073.95188046742, 46974.833734578104, 71637.34343891621, 91699.58392722541, 97046.99934084844, 113188.9080476439, 139362.65242397678, 142555.97232898374, 150410.57979019455, 0, 796.3069822266202, 18288.600265843055, 20514.789132150523, 23069.237009335815, 31274.13704907517, 35302.858107275744, 37073.95188046742, 46974.833734578104, 71637.34343891621, 91699.58392722541, 97046.99934084844, 113188.9080476439, 139362.65242397678, 142555.97232898374, 150410.57979019455, 0, 796.3069822266202, 18288.600265843055, 20514.789132150523, 23069.237009335815, 31274.13704907517, 35302.858107275744, 37073.95188046742, 46974.833734578104, 71637.34343891621, 91699.58392722541, 97046.99934084844, 113188.9080476439, 139362.65242397678, 142555.97232898374, 150410.57979019455, 0, 796.3069822266202, 18288.600265843055, 20514.789132150523, 23069.237009335815, 31274.13704907517, 35302.858107275744, 37073.95188046742, 46974.833734578104, 71637.34343891621, 91699.58392722541, 97046.99934084844, 113188.9080476439, 139362.65242397678, 142555.97232898374, 150410.57979019455], 80)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(80, 80)

np.array_equal(np_weights[0], np_weights[15])

True

np.array_equal(np_weights[0], np_weights[16])

False

Commence training

method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:131.736028194
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:124.616271973
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990518555045 and training accuracy:0.991609752178
validation cost:0.0925189256668 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0539999529719 and training accuracy:0.99287801981
validation cost:0.0477138087153 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0376890674233 and training accuracy:0.994829297066
validation cost:0.0302194636315 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0290481522679 and training accuracy:0.99658536911
validation cost:0.0220831781626 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023657489568 and training accuracy:0.997756123543
validation cost:0.0176057368517 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198712404817 and training accuracy:0.998341441154
validation cost:0.0145276719704 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169922467321 and training accuracy:0.998341441154
validation cost:0.0122214574367 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0153050273657 and training accuracy:0.998146355152
validation cost:0.011213125661 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139560960233 and training accuracy:0.998243927956
validation cost:0.0100094126537 and validation accuracy:1.0
Training on :(4, 5)
Time taken:118.367846012
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636208951473 and training accuracy:0.991611778736
validation cost:0.0635736957192 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0342947021127 and training accuracy:0.996843159199
validation cost:0.0337495431304 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0241673067212 and training accuracy:0.997745096684
validation cost:0.0247216559947 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0191191416234 and training accuracy:0.998015701771
validation cost:0.01931928657 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0155691420659 and training accuracy:0.998286306858
validation cost:0.0159959737211 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0129639329389 and training accuracy:0.9987372756
validation cost:0.0133697763085 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.011112768203 and training accuracy:0.998827457428
validation cost:0.0117992609739 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00979762617499 and training accuracy:0.999007821083
validation cost:0.0101021369919 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00877885892987 and training accuracy:0.999098062515
validation cost:0.00852270238101 and validation accuracy:0.999087572098
Training on :(6, 7)
Time taken:127.797518015
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151477068663 and training accuracy:0.965170443058
validation cost:0.148457437754 and validation accuracy:0.964218437672
Training on :(8, 9)
training cost:0.103641562164 and training accuracy:0.972527444363
validation cost:0.103159971535 and validation accuracy:0.973634660244
Training on :(8, 9)
training cost:0.082123234868 and training accuracy:0.976066291332
validation cost:0.0786714181304 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.069301366806 and training accuracy:0.979791402817
validation cost:0.0627456903458 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0595998130739 and training accuracy:0.982957720757
validation cost:0.0547399930656 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0535054244101 and training accuracy:0.985285878181
validation cost:0.0488348640501 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0479301735759 and training accuracy:0.986775934696
validation cost:0.0455383919179 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0442771986127 and training accuracy:0.987520933151
validation cost:0.0432717837393 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0408748500049 and training accuracy:0.988359093666
validation cost:0.0389142967761 and validation accuracy:0.993408679962
Training on :(8, 9)
Time taken:121.30377388
Method 3 test accuracy:0.78979998827
Training with lmbda:796.306982227, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:133.669653177
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.073874913156 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0564844347537 and training accuracy:0.980729043484
validation cost:0.0583035610616 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0512569919229 and training accuracy:0.98300153017
validation cost:0.0507564842701 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820899069 and training accuracy:0.985546767712
validation cost:0.0472811497748 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0426244996488 and training accuracy:0.987273871899
validation cost:0.041500158608 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:124.287638903
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990266650915 and training accuracy:0.991609752178
validation cost:0.0920302942395 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0540329180658 and training accuracy:0.99287801981
validation cost:0.0478318855166 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.037755984813 and training accuracy:0.994731724262
validation cost:0.0299657285213 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.029135838151 and training accuracy:0.99658536911
validation cost:0.0224184412509 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0236546043307 and training accuracy:0.997756123543
validation cost:0.0179993025959 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198776386678 and training accuracy:0.998341441154
validation cost:0.0146357016638 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169732440263 and training accuracy:0.998341441154
validation cost:0.0122212488204 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0152960475534 and training accuracy:0.998048782349
validation cost:0.0112420255318 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139087866992 and training accuracy:0.998146355152
validation cost:0.0101556610316 and validation accuracy:1.0
Training on :(4, 5)
Time taken:113.786477804
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636147931218 and training accuracy:0.991611778736
validation cost:0.0635578483343 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0341853126884 and training accuracy:0.996933341026
validation cost:0.033898293972 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0241869240999 and training accuracy:0.997745096684
validation cost:0.024723732844 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0191083867103 and training accuracy:0.998015701771
validation cost:0.0193313360214 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0155309373513 and training accuracy:0.998286306858
validation cost:0.0159820858389 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0129935489967 and training accuracy:0.9987372756
validation cost:0.0135570503771 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0110951820388 and training accuracy:0.998827457428
validation cost:0.0116293327883 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00982797984034 and training accuracy:0.999007821083
validation cost:0.0102260839194 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00879415310919 and training accuracy:0.999098062515
validation cost:0.00859204027802 and validation accuracy:0.999087572098
Training on :(6, 7)
Time taken:122.488770962
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.15148922801 and training accuracy:0.965170443058
validation cost:0.148252308369 and validation accuracy:0.96516007185
Training on :(8, 9)
training cost:0.10349150002 and training accuracy:0.972527444363
validation cost:0.102656595409 and validation accuracy:0.973634660244
Training on :(8, 9)
training cost:0.0822133123875 and training accuracy:0.975973188877
validation cost:0.0786989107728 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.0692298561335 and training accuracy:0.979698240757
validation cost:0.0625535920262 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0596315972507 and training accuracy:0.983050823212
validation cost:0.0548168830574 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0535449199378 and training accuracy:0.985192775726
validation cost:0.0488376505673 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0478708669543 and training accuracy:0.986775934696
validation cost:0.0456292182207 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0441715195775 and training accuracy:0.987427830696
validation cost:0.0423408262432 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0409896560013 and training accuracy:0.988359093666
validation cost:0.0396223850548 and validation accuracy:0.992467045784
Training on :(8, 9)
Time taken:119.058594942
Method 3 test accuracy:0.790000021458
Training with lmbda:18288.6002658, 2
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:20514.7891322, 3
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:23069.2370093, 4
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:35302.8581073, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:37073.9518805, 7
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:71637.3434389, 9
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.780499994755
Training with lmbda:97046.9993408, 11
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.781300008297
Training with lmbda:113188.908048, 12
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:18288.6002658, 18
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.682478189
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Training with lmbda:35302.8581073, 22
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:71637.3434389, 25
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.469040155
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91699.5839272, 26
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.943747997
Method 3 test accuracy:0.794799983501
Training with lmbda:97046.9993408, 27
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Repeat:0
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validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0443691536784 and training accuracy:0.987546563148
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Training on :(2, 3)
Time taken:122.426068783
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:113.682409048
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.383770943
Method 3 test accuracy:0.795599997044
Training with lmbda:113188.908048, 28
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
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Valid features:(1088, 3630)
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Repeat:0
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.939203978
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.50605607
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.903088093
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.595140219
Method 3 test accuracy:0.796100020409
Training with lmbda:139362.652424, 29
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.044284965843 and training accuracy:0.987364768982
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Training on :(2, 3)
Time taken:122.889750004
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.362025976
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.795700013638
Training with lmbda:150410.57979, 31
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:18288.6002658, 34
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:126.528137922
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787000000477
Training with lmbda:35302.8581073, 38
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.313584805
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:97046.9993408, 43
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:113188.908048, 44
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 64
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:31274.1370491, 69
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91699.5839272, 74
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:150410.57979, 79
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0406066067517 and training accuracy:0.995314955711
validation cost:0.0420646257699 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0230203382671 and training accuracy:0.995228171349
validation cost:0.0234451759607 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0167031474411 and training accuracy:0.996703088284
validation cost:0.0187955778092 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0130601068959 and training accuracy:0.997657477856
validation cost:0.0140707390383 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0111347502097 and training accuracy:0.998004496098
validation cost:0.0117450542748 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00962120573968 and training accuracy:0.99809128046
validation cost:0.0109322778881 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.00838874466717 and training accuracy:0.998264789581
validation cost:0.0101041002199 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.00755478534847 and training accuracy:0.99809128046
validation cost:0.00917085818946 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00698435213417 and training accuracy:0.998004496098
validation cost:0.00852664839476 and validation accuracy:0.995610177517
Training on :(0, 1)
Time taken:129.14598918
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.171867415309 and training accuracy:0.947277545929
validation cost:0.173728704453 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.115142084658 and training accuracy:0.968366503716
validation cost:0.11946169287 and validation accuracy:0.963235318661
Training on :(2, 3)
training cost:0.0912334695458 and training accuracy:0.971911668777
validation cost:0.0963196977973 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0758773386478 and training accuracy:0.975184082985
validation cost:0.0819409862161 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0650301128626 and training accuracy:0.978910982609
validation cost:0.0661897957325 and validation accuracy:0.978860318661
Training on :(2, 3)
training cost:0.0579166002572 and training accuracy:0.981819808483
validation cost:0.0601777881384 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0518716499209 and training accuracy:0.984183251858
validation cost:0.0546671636403 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.0477607734501 and training accuracy:0.985637664795
validation cost:0.0519828945398 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0442180261016 and training accuracy:0.986546695232
validation cost:0.0472717024386 and validation accuracy:0.985294103622
Training on :(2, 3)
Time taken:123.922990084
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0942338854074 and training accuracy:0.99356096983
validation cost:0.0833205655217 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0534335225821 and training accuracy:0.992975592613
validation cost:0.0437034852803 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0380345359445 and training accuracy:0.994829297066
validation cost:0.0298542045057 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0293156262487 and training accuracy:0.996292710304
validation cost:0.0226040203124 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0242770463228 and training accuracy:0.997170746326
validation cost:0.0179096739739 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0210908483714 and training accuracy:0.997170746326
validation cost:0.0143040930852 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0186501797289 and training accuracy:0.99726831913
validation cost:0.0125527568161 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0168809853494 and training accuracy:0.99726831913
validation cost:0.0109459878877 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0154427085072 and training accuracy:0.997365832329
validation cost:0.00964786857367 and validation accuracy:1.0
Training on :(4, 5)
Time taken:115.303545952
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0628984123468 and training accuracy:0.991070628166
validation cost:0.063825070858 and validation accuracy:0.989963531494
Training on :(6, 7)
training cost:0.0348196551204 and training accuracy:0.996662735939
validation cost:0.0345997363329 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0249034110457 and training accuracy:0.997745096684
validation cost:0.0257864333689 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0197375100106 and training accuracy:0.997474491596
validation cost:0.0202731899917 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0160844363272 and training accuracy:0.997654914856
validation cost:0.0171464588493 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0139067452401 and training accuracy:0.998015701771
validation cost:0.014165555127 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0121061690152 and training accuracy:0.998196065426
validation cost:0.0126896938309 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0108507405967 and training accuracy:0.998466670513
validation cost:0.0114799691364 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.00980369281024 and training accuracy:0.9987372756
validation cost:0.00978200417012 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:124.747390032
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.152182772756 and training accuracy:0.967405498028
validation cost:0.14825540781 and validation accuracy:0.972693026066
Training on :(8, 9)
training cost:0.103497989476 and training accuracy:0.971875607967
validation cost:0.102435767651 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0826212540269 and training accuracy:0.975973188877
validation cost:0.0839911326766 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0695876404643 and training accuracy:0.980536401272
validation cost:0.0690471231937 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0611535422504 and training accuracy:0.982957720757
validation cost:0.0599372349679 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0541753582656 and training accuracy:0.984633982182
validation cost:0.0513844527304 and validation accuracy:0.98681730032
Training on :(8, 9)
training cost:0.0496257953346 and training accuracy:0.985379040241
validation cost:0.0474896170199 and validation accuracy:0.989642202854
Training on :(8, 9)
training cost:0.0457387007773 and training accuracy:0.986869037151
validation cost:0.0445782802999 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0426873117685 and training accuracy:0.988265991211
validation cost:0.0424122400582 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:120.618019104
Method 3 test accuracy:0.777199983597

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_16lmbdas_ar1_3lyrs_he1_v2.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7900	796.306982
2	0.7824	18288.600266
3	0.7821	20514.789132
4	0.7814	23069.237009
5	0.7831	31274.137049
6	0.7831	35302.858107
7	0.7829	37073.951880
8	0.7823	46974.833735
9	0.7810	71637.343439
10	0.7805	91699.583927
11	0.7813	97046.999341
12	0.7802	113188.908048
13	0.7905	139362.652424
14	0.7816	142555.972329
15	0.7879	150410.579790
16	0.7927	0.000000
17	0.7912	796.306982
18	0.7918	18288.600266
19	0.7859	20514.789132
20	0.7860	23069.237009
21	0.7925	31274.137049
22	0.7884	35302.858107
23	0.7880	37073.951880
24	0.7925	46974.833735
25	0.7939	71637.343439
26	0.7948	91699.583927
27	0.7956	97046.999341
28	0.7961	113188.908048
29	0.7940	139362.652424
...	...	...
50	0.7867	18288.600266
51	0.7900	20514.789132
52	0.7907	23069.237009
53	0.7906	31274.137049
54	0.7920	35302.858107
55	0.7971	37073.951880
56	0.7893	46974.833735
57	0.7896	71637.343439
58	0.7974	91699.583927
59	0.7902	97046.999341
60	0.7906	113188.908048
61	0.7893	139362.652424
62	0.7902	142555.972329
63	0.7897	150410.579790
64	0.7784	0.000000
65	0.7788	796.306982
66	0.7782	18288.600266
67	0.7783	20514.789132
68	0.7778	23069.237009
69	0.7777	31274.137049
70	0.7784	35302.858107
71	0.7788	37073.951880
72	0.7789	46974.833735
73	0.7790	71637.343439
74	0.7785	91699.583927
75	0.7786	97046.999341
76	0.7777	113188.908048
77	0.7776	139362.652424
78	0.7775	142555.972329
79	0.7772	150410.579790

80 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
mean_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
display(mean_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.78762
796.306982	0.78738
18288.600266	0.78516
20514.789132	0.78470
23069.237009	0.78456
31274.137049	0.78618
35302.858107	0.78568
37073.951880	0.78656
46974.833735	0.78600
71637.343439	0.78616
91699.583927	0.78782
97046.999341	0.78670
113188.908048	0.78644
139362.652424	0.78776
142555.972329	0.78650
150410.579790	0.78740

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
std_acc_grouped_by_lmbda = acc_grouped_by_lmbda.std()
display(std_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.005442
796.306982	0.004962
18288.600266	0.005121
20514.789132	0.004569
23069.237009	0.005023
31274.137049	0.005949
35302.858107	0.005188
37073.951880	0.006839
46974.833735	0.005437
71637.343439	0.006143
91699.583927	0.008381
97046.999341	0.006845
113188.908048	0.007538
139362.652424	0.006168
142555.972329	0.007147
150410.579790	0.006381

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
max_acc_grouped_by_lmbda = acc_grouped_by_lmbda.max()
display(max_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.7927
796.306982	0.7912
18288.600266	0.7918
20514.789132	0.7900
23069.237009	0.7907
31274.137049	0.7925
35302.858107	0.7920
37073.951880	0.7971
46974.833735	0.7925
71637.343439	0.7939
91699.583927	0.7974
97046.999341	0.7956
113188.908048	0.7961
139362.652424	0.7940
142555.972329	0.7957
150410.579790	0.7947

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

mean_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

Init the $\lambda$s with (7.5, 10)

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_15lmbdas_ar1_3lyrs_he1_75_10_no_exp', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 15
a = np.random.uniform(low=7.5, high=10, size=(n_lmbdas,))
print(a)
print()
a = a[np.argsort(a)]
print(a)
print()
n_reps = 5
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[8.85851235 8.19592346 8.56129398 9.61194033 7.51179714 7.8039228
 9.17687271 9.56463189 7.84176647 8.93773332 9.72830489 8.02300531
 7.96332055 7.77094223 8.04924373]
()
[7.51179714 7.77094223 7.8039228  7.84176647 7.96332055 8.02300531
 8.04924373 8.19592346 8.56129398 8.85851235 8.93773332 9.17687271
 9.56463189 9.61194033 9.72830489]
()
([0, 7.511797140477431, 7.770942226160638, 7.8039228019577855, 7.841766474212382, 7.9633205488751875, 8.023005305292974, 8.04924373156248, 8.195923462734491, 8.561293976872832, 8.858512354477414, 8.937733323568125, 9.176872711816946, 9.56463188776262, 9.61194033079976, 9.728304885780659, 0, 7.511797140477431, 7.770942226160638, 7.8039228019577855, 7.841766474212382, 7.9633205488751875, 8.023005305292974, 8.04924373156248, 8.195923462734491, 8.561293976872832, 8.858512354477414, 8.937733323568125, 9.176872711816946, 9.56463188776262, 9.61194033079976, 9.728304885780659, 0, 7.511797140477431, 7.770942226160638, 7.8039228019577855, 7.841766474212382, 7.9633205488751875, 8.023005305292974, 8.04924373156248, 8.195923462734491, 8.561293976872832, 8.858512354477414, 8.937733323568125, 9.176872711816946, 9.56463188776262, 9.61194033079976, 9.728304885780659, 0, 7.511797140477431, 7.770942226160638, 7.8039228019577855, 7.841766474212382, 7.9633205488751875, 8.023005305292974, 8.04924373156248, 8.195923462734491, 8.561293976872832, 8.858512354477414, 8.937733323568125, 9.176872711816946, 9.56463188776262, 9.61194033079976, 9.728304885780659, 0, 7.511797140477431, 7.770942226160638, 7.8039228019577855, 7.841766474212382, 7.9633205488751875, 8.023005305292974, 8.04924373156248, 8.195923462734491, 8.561293976872832, 8.858512354477414, 8.937733323568125, 9.176872711816946, 9.56463188776262, 9.61194033079976, 9.728304885780659], 80)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(80, 80)

np.array_equal(np_weights[0], np_weights[15])

True

np.array_equal(np_weights[0], np_weights[16])

False

Commence training

method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:137.231850863
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:128.123242855
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990518555045 and training accuracy:0.991609752178
validation cost:0.0925189256668 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0539999529719 and training accuracy:0.99287801981
validation cost:0.0477138087153 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0376890674233 and training accuracy:0.994829297066
validation cost:0.0302194636315 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0290481522679 and training accuracy:0.99658536911
validation cost:0.0220831781626 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023657489568 and training accuracy:0.997756123543
validation cost:0.0176057368517 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198712404817 and training accuracy:0.998341441154
validation cost:0.0145276719704 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169922467321 and training accuracy:0.998341441154
validation cost:0.0122214574367 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0153050273657 and training accuracy:0.998146355152
validation cost:0.011213125661 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139560960233 and training accuracy:0.998243927956
validation cost:0.0100094126537 and validation accuracy:1.0
Training on :(4, 5)
Time taken:116.586731195
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636208951473 and training accuracy:0.991611778736
validation cost:0.0635736957192 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0342947021127 and training accuracy:0.996843159199
validation cost:0.0337495431304 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0241673067212 and training accuracy:0.997745096684
validation cost:0.0247216559947 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0191191416234 and training accuracy:0.998015701771
validation cost:0.01931928657 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0155691420659 and training accuracy:0.998286306858
validation cost:0.0159959737211 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0129639329389 and training accuracy:0.9987372756
validation cost:0.0133697763085 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.011112768203 and training accuracy:0.998827457428
validation cost:0.0117992609739 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00979762617499 and training accuracy:0.999007821083
validation cost:0.0101021369919 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00877885892987 and training accuracy:0.999098062515
validation cost:0.00852270238101 and validation accuracy:0.999087572098
Training on :(6, 7)
Time taken:123.331638098
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151477068663 and training accuracy:0.965170443058
validation cost:0.148457437754 and validation accuracy:0.964218437672
Training on :(8, 9)
training cost:0.103641562164 and training accuracy:0.972527444363
validation cost:0.103159971535 and validation accuracy:0.973634660244
Training on :(8, 9)
training cost:0.082123234868 and training accuracy:0.976066291332
validation cost:0.0786714181304 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.069301366806 and training accuracy:0.979791402817
validation cost:0.0627456903458 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0595998130739 and training accuracy:0.982957720757
validation cost:0.0547399930656 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0535054244101 and training accuracy:0.985285878181
validation cost:0.0488348640501 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0479301735759 and training accuracy:0.986775934696
validation cost:0.0455383919179 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0442771986127 and training accuracy:0.987520933151
validation cost:0.0432717837393 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0408748500049 and training accuracy:0.988359093666
validation cost:0.0389142967761 and validation accuracy:0.993408679962
Training on :(8, 9)
Time taken:119.170996189
Method 3 test accuracy:0.78979998827
Training with lmbda:7.51179714048, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:127.932966948
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:122.498989105
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
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Training on :(2, 3)
Time taken:122.857856989
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:7.96332054888, 5
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.02300530529, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
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Training on :(2, 3)
Time taken:122.618960142
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.19592346273, 8
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.85851235448, 10
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:9.72830488578, 15
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.680936813
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.352900028
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.05966711
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.04924373156, 23
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.56129397687, 25
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.56129397687, 41
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.595708847
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.82083416
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:120.029114008
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Training with lmbda:7.51179714048, 49
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0416168235242 and training accuracy:0.987092077732
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Training on :(2, 3)
Time taken:122.439929008
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.667946815
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Repeat:0
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.489090204
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.805668831
Method 3 test accuracy:0.789699971676
Training with lmbda:7.77094222616, 50
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Train features:(11001, 3630)
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Valid features:(1088, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.063141108
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0091879600659 and training accuracy:0.998827457428
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Training on :(6, 7)
Time taken:123.761116028
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.05650402233 and training accuracy:0.983795881271
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0428918749094 and training accuracy:0.987707197666
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Training on :(8, 9)
Time taken:119.880573034
Method 3 test accuracy:0.789699971676
Training with lmbda:7.80392280196, 51
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Repeat:0
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validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0416168235242 and training accuracy:0.987092077732
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Training on :(2, 3)
Time taken:122.56014204
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.547981977
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.297685146
Method 3 test accuracy:0.789699971676
Training with lmbda:7.84176647421, 52
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Valid features:(1088, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.630732059
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.312396049
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.160474062
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.789699971676
Training with lmbda:7.96332054888, 53
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.682887077
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.127099991
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0416168235242 and training accuracy:0.987092077732
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Training on :(2, 3)
Time taken:122.257332087
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.652070999
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.04924373156, 55
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.427983046
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.661303043
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.789699971676
Training with lmbda:8.56129397687, 57
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.85851235448, 58
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0416168235242 and training accuracy:0.987092077732
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Training on :(2, 3)
Time taken:122.530841827
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.778800010681
Training with lmbda:8.19592346273, 72
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:8.56129397687, 73
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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validation cost:0.0819085538387 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0653025358915 and training accuracy:0.979456424713
validation cost:0.0665035769343 and validation accuracy:0.978860318661
Training on :(2, 3)
training cost:0.0580889172852 and training accuracy:0.9817289114
validation cost:0.0606088973582 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0521769523621 and training accuracy:0.984092354774
validation cost:0.0547606013715 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.0476460047066 and training accuracy:0.985728561878
validation cost:0.0518938750029 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0443670004606 and training accuracy:0.986728489399
validation cost:0.0479844585061 and validation accuracy:0.985294103622
Training on :(2, 3)
Time taken:127.695600986
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0943072885275 and training accuracy:0.993463397026
validation cost:0.083395473659 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.053331580013 and training accuracy:0.993073165417
validation cost:0.0433798357844 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0374968871474 and training accuracy:0.994829297066
validation cost:0.0288449414074 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0288092717528 and training accuracy:0.996390223503
validation cost:0.0221864599735 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0239357799292 and training accuracy:0.996975600719
validation cost:0.0179479662329 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0206256192178 and training accuracy:0.997170746326
validation cost:0.0143882324919 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0181834287941 and training accuracy:0.99726831913
validation cost:0.0119842672721 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0161860194057 and training accuracy:0.997463405132
validation cost:0.010232088156 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0147315105423 and training accuracy:0.997463405132
validation cost:0.0089998356998 and validation accuracy:1.0
Training on :(4, 5)
Time taken:128.08463192
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0629686638713 and training accuracy:0.990709841251
validation cost:0.063085667789 and validation accuracy:0.989963531494
Training on :(6, 7)
training cost:0.0347865857184 and training accuracy:0.996572554111
validation cost:0.0342171937227 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0245375912637 and training accuracy:0.997474491596
validation cost:0.0253121834248 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0194008480757 and training accuracy:0.997474491596
validation cost:0.0205389261246 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0156705435365 and training accuracy:0.997745096684
validation cost:0.0162374582142 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0135167920962 and training accuracy:0.997925519943
validation cost:0.0137619227171 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0116283893585 and training accuracy:0.998376488686
validation cost:0.0124588711187 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0104563068599 and training accuracy:0.998466670513
validation cost:0.0107550639659 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.00935703516006 and training accuracy:0.998827457428
validation cost:0.00940547138453 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:126.197345972
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151710405946 and training accuracy:0.966474175453
validation cost:0.14873893559 and validation accuracy:0.970809817314
Training on :(8, 9)
training cost:0.102404296398 and training accuracy:0.972713708878
validation cost:0.101458370686 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0814551189542 and training accuracy:0.976438820362
validation cost:0.0819562450051 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0689082965255 and training accuracy:0.980722665787
validation cost:0.0689102709293 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0609489642084 and training accuracy:0.982771456242
validation cost:0.0598627887666 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0537236705422 and training accuracy:0.984633982182
validation cost:0.0510799326003 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0490582250059 and training accuracy:0.985751509666
validation cost:0.0490953698754 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0447834059596 and training accuracy:0.987800359726
validation cost:0.0450638979673 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0413905642927 and training accuracy:0.987800359726
validation cost:0.0411700382829 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:122.943760872
Method 3 test accuracy:0.778800010681
Training with lmbda:9.72830488578, 79
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0406066067517 and training accuracy:0.995314955711
validation cost:0.0420646257699 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0230203382671 and training accuracy:0.995228171349
validation cost:0.0234451759607 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0167031474411 and training accuracy:0.996703088284
validation cost:0.0187955778092 and validation accuracy:0.994732201099
Training on :(0, 1)
training cost:0.0130601068959 and training accuracy:0.997657477856
validation cost:0.0140707390383 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0111347502097 and training accuracy:0.998004496098
validation cost:0.0117450542748 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00962120573968 and training accuracy:0.99809128046
validation cost:0.0109322778881 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.00838874466717 and training accuracy:0.998264789581
validation cost:0.0101041002199 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.00755478534847 and training accuracy:0.99809128046
validation cost:0.00917085818946 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00698435213417 and training accuracy:0.998004496098
validation cost:0.00852664839476 and validation accuracy:0.995610177517
Training on :(0, 1)
Time taken:129.840866089
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.171883046627 and training accuracy:0.947368443012
validation cost:0.173870489001 and validation accuracy:0.943933844566
Training on :(2, 3)
training cost:0.115301266313 and training accuracy:0.968275606632
validation cost:0.11939971894 and validation accuracy:0.963235318661
Training on :(2, 3)
training cost:0.0913520008326 and training accuracy:0.971911668777
validation cost:0.096379943192 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0760460272431 and training accuracy:0.975184082985
validation cost:0.0819085538387 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0653025358915 and training accuracy:0.979456424713
validation cost:0.0665035769343 and validation accuracy:0.978860318661
Training on :(2, 3)
training cost:0.0580889172852 and training accuracy:0.9817289114
validation cost:0.0606088973582 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0521769523621 and training accuracy:0.984092354774
validation cost:0.0547606013715 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.0476460047066 and training accuracy:0.985728561878
validation cost:0.0518938750029 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0443670004606 and training accuracy:0.986728489399
validation cost:0.0479844585061 and validation accuracy:0.985294103622
Training on :(2, 3)
Time taken:122.104948044
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0943072885275 and training accuracy:0.993463397026
validation cost:0.083395473659 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.053331580013 and training accuracy:0.993073165417
validation cost:0.0433798357844 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0374968871474 and training accuracy:0.994829297066
validation cost:0.0288449414074 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0288092717528 and training accuracy:0.996390223503
validation cost:0.0221864599735 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0239357799292 and training accuracy:0.996975600719
validation cost:0.0179479662329 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0206256192178 and training accuracy:0.997170746326
validation cost:0.0143882324919 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0181834287941 and training accuracy:0.99726831913
validation cost:0.0119842672721 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0161860194057 and training accuracy:0.997463405132
validation cost:0.010232088156 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0147315105423 and training accuracy:0.997463405132
validation cost:0.0089998356998 and validation accuracy:1.0
Training on :(4, 5)
Time taken:118.03403616
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0629686638713 and training accuracy:0.990709841251
validation cost:0.063085667789 and validation accuracy:0.989963531494
Training on :(6, 7)
training cost:0.0347865857184 and training accuracy:0.996572554111
validation cost:0.0342171937227 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0245375912637 and training accuracy:0.997474491596
validation cost:0.0253121834248 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0194008480757 and training accuracy:0.997474491596
validation cost:0.0205389261246 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0156705435365 and training accuracy:0.997745096684
validation cost:0.0162374582142 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0135167920962 and training accuracy:0.997925519943
validation cost:0.0137619227171 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0116283893585 and training accuracy:0.998376488686
validation cost:0.0124588711187 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0104563068599 and training accuracy:0.998466670513
validation cost:0.0107550639659 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.00935703516006 and training accuracy:0.998827457428
validation cost:0.00940547138453 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:128.826741934
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151710405946 and training accuracy:0.966474175453
validation cost:0.14873893559 and validation accuracy:0.970809817314
Training on :(8, 9)
training cost:0.102404296398 and training accuracy:0.972713708878
validation cost:0.101458370686 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0814551189542 and training accuracy:0.976438820362
validation cost:0.0819562450051 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0689082965255 and training accuracy:0.980722665787
validation cost:0.0689102709293 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0609489642084 and training accuracy:0.982771456242
validation cost:0.0598627887666 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0537236705422 and training accuracy:0.984633982182
validation cost:0.0510799326003 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0490582250059 and training accuracy:0.985751509666
validation cost:0.0490953698754 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0447834059596 and training accuracy:0.987800359726
validation cost:0.0450638979673 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0413905642927 and training accuracy:0.987800359726
validation cost:0.0411700382829 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:122.543135881
Method 3 test accuracy:0.778800010681

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_15lmbdas_ar1_3lyrs_he1_75_10_noexp.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7904	7.511797
2	0.7904	7.770942
3	0.7904	7.803923
4	0.7904	7.841766
5	0.7904	7.963321
6	0.7904	8.023005
7	0.7904	8.049244
8	0.7904	8.195923
9	0.7900	8.561294
10	0.7900	8.858512
11	0.7900	8.937733
12	0.7900	9.176873
13	0.7900	9.564632
14	0.7900	9.611940
15	0.7900	9.728305
16	0.7927	0.000000
17	0.7911	7.511797
18	0.7911	7.770942
19	0.7911	7.803923
20	0.7911	7.841766
21	0.7911	7.963321
22	0.7911	8.023005
23	0.7911	8.049244
24	0.7911	8.195923
25	0.7911	8.561294
26	0.7911	8.858512
27	0.7911	8.937733
28	0.7911	9.176873
29	0.7911	9.564632
...	...	...
50	0.7897	7.770942
51	0.7897	7.803923
52	0.7897	7.841766
53	0.7897	7.963321
54	0.7897	8.023005
55	0.7897	8.049244
56	0.7897	8.195923
57	0.7897	8.561294
58	0.7897	8.858512
59	0.7897	8.937733
60	0.7897	9.176873
61	0.7898	9.564632
62	0.7898	9.611940
63	0.7897	9.728305
64	0.7784	0.000000
65	0.7788	7.511797
66	0.7788	7.770942
67	0.7788	7.803923
68	0.7788	7.841766
69	0.7788	7.963321
70	0.7788	8.023005
71	0.7788	8.049244
72	0.7788	8.195923
73	0.7788	8.561294
74	0.7788	8.858512
75	0.7788	8.937733
76	0.7788	9.176873
77	0.7788	9.564632
78	0.7788	9.611940
79	0.7788	9.728305

80 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
mean_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
display(mean_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.78762
7.511797	0.78752
7.770942	0.78752
7.803923	0.78752
7.841766	0.78752
7.963321	0.78752
8.023005	0.78752
8.049244	0.78752
8.195923	0.78754
8.561294	0.78746
8.858512	0.78746
8.937733	0.78746
9.176873	0.78746
9.564632	0.78748
9.611940	0.78748
9.728305	0.78746

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
std_acc_grouped_by_lmbda = acc_grouped_by_lmbda.std()
display(std_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.005442
7.511797	0.005047
7.770942	0.005047
7.803923	0.005047
7.841766	0.005047
7.963321	0.005047
8.023005	0.005047
8.049244	0.005047
8.195923	0.005048
8.561294	0.004994
8.858512	0.004994
8.937733	0.004994
9.176873	0.004994
9.564632	0.005006
9.611940	0.005006
9.728305	0.004994

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
max_acc_grouped_by_lmbda = acc_grouped_by_lmbda.max()
display(max_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.7927
7.511797	0.7911
7.770942	0.7911
7.803923	0.7911
7.841766	0.7911
7.963321	0.7911
8.023005	0.7911
8.049244	0.7911
8.195923	0.7911
8.561294	0.7911
8.858512	0.7911
8.937733	0.7911
9.176873	0.7911
9.564632	0.7911
9.611940	0.7911
9.728305	0.7911

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

mean_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

Init the writer with $\lambda$s with (7.5, 10)e4

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_11lmbdas_ar1_3lyrs_he1_75_10', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 11
a = np.random.uniform(low=7.5, high=10.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 5
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[8.85851235 8.19592346 8.56129398 9.61194033 7.51179714 7.8039228
 9.17687271 9.56463189 7.84176647 8.93773332 9.72830489]
()
[75117.97140477 78039.22801958 78417.66474212 81959.23462734
 85612.93976873 88585.12354477 89377.33323568 91768.72711817
 95646.31887763 96119.403308   97283.04885781]
()
([0, 75117.9714047743, 78039.22801957786, 78417.66474212382, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 78039.22801957786, 78417.66474212382, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 78039.22801957786, 78417.66474212382, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 78039.22801957786, 78417.66474212382, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 78039.22801957786, 78417.66474212382, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659], 60)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(60, 60)

np.array_equal(np_weights[0], np_weights[11])

True

np.array_equal(np_weights[0], np_weights[12])

False

Commence training

method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:127.73784399
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:121.860054016
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990518555045 and training accuracy:0.991609752178
validation cost:0.0925189256668 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0539999529719 and training accuracy:0.99287801981
validation cost:0.0477138087153 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0376890674233 and training accuracy:0.994829297066
validation cost:0.0302194636315 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0290481522679 and training accuracy:0.99658536911
validation cost:0.0220831781626 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023657489568 and training accuracy:0.997756123543
validation cost:0.0176057368517 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198712404817 and training accuracy:0.998341441154
validation cost:0.0145276719704 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169922467321 and training accuracy:0.998341441154
validation cost:0.0122214574367 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0153050273657 and training accuracy:0.998146355152
validation cost:0.011213125661 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139560960233 and training accuracy:0.998243927956
validation cost:0.0100094126537 and validation accuracy:1.0
Training on :(4, 5)
Time taken:113.461678982
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636208951473 and training accuracy:0.991611778736
validation cost:0.0635736957192 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0342947021127 and training accuracy:0.996843159199
validation cost:0.0337495431304 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0241673067212 and training accuracy:0.997745096684
validation cost:0.0247216559947 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0191191416234 and training accuracy:0.998015701771
validation cost:0.01931928657 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0155691420659 and training accuracy:0.998286306858
validation cost:0.0159959737211 and validation accuracy:0.996350347996
Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78039.2280196, 2
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78417.6647421, 3
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:81959.2346273, 4
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.7799000144
Training with lmbda:89377.3332357, 7
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.780499994755
Training with lmbda:91768.7271182, 8
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75117.9714048, 13
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:88585.1235448, 18
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:113.455426931
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.74334693
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:96119.403308, 22
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.537163019
Method 3 test accuracy:0.794799983501
Training with lmbda:97283.0488578, 23
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:113.913383961
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.955150127
Method 3 test accuracy:0.787500023842
Training with lmbda:78039.2280196, 26
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.479188919
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.692214966
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787299990654
Training with lmbda:78417.6647421, 27
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.638926029
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0417045652866 and training accuracy:0.988172829151
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Training on :(8, 9)
Time taken:119.049803972
Method 3 test accuracy:0.787400007248
Training with lmbda:81959.2346273, 28
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Repeat:0
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0423688963056 and training accuracy:0.986819386482
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Training on :(2, 3)
Time taken:121.610131979
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0144930640236 and training accuracy:0.998439013958
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Training on :(4, 5)
Time taken:113.800564051
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.255800962
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.046588182
Method 3 test accuracy:0.787800014019
Training with lmbda:85612.9397687, 29
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
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Valid features:(1088, 3630)
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Repeat:0
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0424053296447 and training accuracy:0.986819386482
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Training on :(2, 3)
Time taken:121.552802086
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:114.301076174
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.372384071
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.055798054
Method 3 test accuracy:0.787400007248
Training with lmbda:88585.1235448, 30
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0423813350499 and training accuracy:0.986910283566
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Training on :(2, 3)
Time taken:121.69587779
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91768.7271182, 32
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:96119.403308, 34
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:129.050164223
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:85612.9397687, 41
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.11205101
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:88585.1235448, 42
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.33345294
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.783366919
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91768.7271182, 56
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:95646.3188776, 57
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0107637597248 and training accuracy:0.998466670513
validation cost:0.0113717783242 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.00964837148786 and training accuracy:0.998917639256
validation cost:0.00956209935248 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:122.729166031
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
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validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
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validation cost:0.148056328297 and validation accuracy:0.971751391888
Training on :(8, 9)
training cost:0.103241428733 and training accuracy:0.971503078938
validation cost:0.10190666467 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0821164548397 and training accuracy:0.975786924362
validation cost:0.0813427641988 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0691803172231 and training accuracy:0.980722665787
validation cost:0.0689980238676 and validation accuracy:0.984934091568
Training on :(8, 9)
training cost:0.0610778555274 and training accuracy:0.982771456242
validation cost:0.0598981045187 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0537727922201 and training accuracy:0.985006511211
validation cost:0.0509139299393 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0493482761085 and training accuracy:0.985844671726
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Training on :(8, 9)
training cost:0.0452905148268 and training accuracy:0.987427830696
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Training on :(8, 9)
training cost:0.0418934859335 and training accuracy:0.988079726696
validation cost:0.0414292216301 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:118.704811811
Method 3 test accuracy:0.778299987316
Training with lmbda:96119.403308, 58
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
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validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
training cost:0.0167031474411 and training accuracy:0.996703088284
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Training on :(0, 1)
training cost:0.0130601068959 and training accuracy:0.997657477856
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
training cost:0.00698435213417 and training accuracy:0.998004496098
validation cost:0.00852664839476 and validation accuracy:0.995610177517
Training on :(0, 1)
Time taken:127.823379993
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
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Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
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validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
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Training on :(2, 3)
training cost:0.115139655769 and training accuracy:0.968366503716
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.052261095494 and training accuracy:0.984183251858
validation cost:0.0546778701246 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.0477102473378 and training accuracy:0.985819458961
validation cost:0.0518682710826 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0445268563926 and training accuracy:0.986637592316
validation cost:0.0467901043594 and validation accuracy:0.986213207245
Training on :(2, 3)
Time taken:123.697251081
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0242636781186 and training accuracy:0.996975600719
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0164934676141 and training accuracy:0.997365832329
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Training on :(4, 5)
training cost:0.0152515480295 and training accuracy:0.99726831913
validation cost:0.00944033078849 and validation accuracy:1.0
Training on :(4, 5)
Time taken:117.82909894
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0096881724894 and training accuracy:0.998827457428
validation cost:0.00962863955647 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:123.12809515
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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validation cost:0.0507925078273 and validation accuracy:0.98681730032
Training on :(8, 9)
training cost:0.0490598864853 and training accuracy:0.986124038696
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Training on :(8, 9)
training cost:0.0450154282153 and training accuracy:0.987334728241
validation cost:0.0439847894013 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0422667302191 and training accuracy:0.988172829151
validation cost:0.0411340594292 and validation accuracy:0.991525411606
Training on :(8, 9)
Time taken:118.883975029
Method 3 test accuracy:0.778100013733
Training with lmbda:97283.0488578, 59
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
training cost:0.0167031474411 and training accuracy:0.996703088284
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
training cost:0.00698435213417 and training accuracy:0.998004496098
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Training on :(0, 1)
Time taken:127.606486797
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
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Repeat:0
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.115139655769 and training accuracy:0.968366503716
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0650246366858 and training accuracy:0.979001879692
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0444001480937 and training accuracy:0.986455798149
validation cost:0.0476992577314 and validation accuracy:0.984375
Training on :(2, 3)
Time taken:121.938039064
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0185519829392 and training accuracy:0.997365832329
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0153496703133 and training accuracy:0.997170746326
validation cost:0.00945950765163 and validation accuracy:1.0
Training on :(4, 5)
Time taken:113.623682976
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0120217790827 and training accuracy:0.998196065426
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.00967156887054 and training accuracy:0.998917639256
validation cost:0.00966014899313 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:122.59633708
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
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Training on :(8, 9)
training cost:0.151787027717 and training accuracy:0.967126071453
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Training on :(8, 9)
training cost:0.103641495109 and training accuracy:0.971503078938
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Training on :(8, 9)
training cost:0.0821932405233 and training accuracy:0.975880026817
validation cost:0.0822192654014 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0694462656975 and training accuracy:0.980350136757
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Training on :(8, 9)
training cost:0.0611344799399 and training accuracy:0.982864618301
validation cost:0.0598116703331 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0539418645203 and training accuracy:0.984727144241
validation cost:0.0507767125964 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.049272030592 and training accuracy:0.985844671726
validation cost:0.0467891916633 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0451683625579 and training accuracy:0.987520933151
validation cost:0.0441817715764 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0422247238457 and training accuracy:0.988079726696
validation cost:0.0418000891805 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:118.990875006
Method 3 test accuracy:0.778599977493

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_11lmbdas_ar1_3lyrs_he1_75_10.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7810	75117.971405
2	0.7806	78039.228020
3	0.7811	78417.664742
4	0.7802	81959.234627
5	0.7807	85612.939769
6	0.7799	88585.123545
7	0.7805	89377.333236
8	0.7806	91768.727118
9	0.7889	95646.318878
10	0.7802	96119.403308
11	0.7809	97283.048858
12	0.7927	0.000000
13	0.7939	75117.971405
14	0.7944	78039.228020
15	0.7942	78417.664742
16	0.7946	81959.234627
17	0.7946	85612.939769
18	0.7940	88585.123545
19	0.7942	89377.333236
20	0.7943	91768.727118
21	0.7947	95646.318878
22	0.7948	96119.403308
23	0.7952	97283.048858
24	0.7879	0.000000
25	0.7875	75117.971405
26	0.7873	78039.228020
27	0.7874	78417.664742
28	0.7878	81959.234627
29	0.7874	85612.939769
30	0.7871	88585.123545
31	0.7875	89377.333236
32	0.7876	91768.727118
33	0.7879	95646.318878
34	0.7879	96119.403308
35	0.7873	97283.048858
36	0.7893	0.000000
37	0.7847	75117.971405
38	0.7968	78039.228020
39	0.8064	78417.664742
40	0.7917	81959.234627
41	0.7973	85612.939769
42	0.7976	88585.123545
43	0.7969	89377.333236
44	0.7976	91768.727118
45	0.7896	95646.318878
46	0.7978	96119.403308
47	0.7976	97283.048858
48	0.7784	0.000000
49	0.7795	75117.971405
50	0.7784	78039.228020
51	0.7790	78417.664742
52	0.7786	81959.234627
53	0.7789	85612.939769
54	0.7789	88585.123545
55	0.7783	89377.333236
56	0.7782	91768.727118
57	0.7783	95646.318878
58	0.7781	96119.403308
59	0.7786	97283.048858

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
mean_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
display(mean_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.78762
75117.971405	0.78532
78039.228020	0.78750
78417.664742	0.78962
81959.234627	0.78658
85612.939769	0.78778
88585.123545	0.78750
89377.333236	0.78748
91768.727118	0.78766
95646.318878	0.78788
96119.403308	0.78776
97283.048858	0.78792

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
std_acc_grouped_by_lmbda = acc_grouped_by_lmbda.std()
display(std_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.005442
75117.971405	0.005729
78039.228020	0.008133
78417.664742	0.011100
81959.234627	0.007007
85612.939769	0.008159
88585.123545	0.008309
89377.333236	0.008168
91768.727118	0.008400
95646.318878	0.005964
96119.403308	0.008673
97283.048858	0.008415

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
max_acc_grouped_by_lmbda = acc_grouped_by_lmbda.max()
display(max_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.7927
75117.971405	0.7939
78039.228020	0.7968
78417.664742	0.8064
81959.234627	0.7946
85612.939769	0.7973
88585.123545	0.7976
89377.333236	0.7969
91768.727118	0.7976
95646.318878	0.7947
96119.403308	0.7978
97283.048858	0.7976

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

mean_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

max_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

Init the writer with $\lambda$s (7.5, 8.75)

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_11lmbdas_ar1_3lyrs_he1_75_875', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 11
a = np.random.uniform(low=7.5, high=8.75, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 5
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[8.17925618 7.84796173 8.03064699 8.55597017 7.50589857 7.6519614
 8.33843636 8.53231594 7.67088324 8.21886666 8.61415244]
()
[75058.98570239 76519.61400979 76708.83237106 78479.61731367
 80306.46988436 81792.56177239 82188.66661784 83384.36355908
 85323.15943881 85559.701654   86141.5244289 ]
()
([0, 75058.98570238716, 76519.61400978893, 76708.83237106192, 78479.61731367245, 80306.46988436417, 81792.56177238707, 82188.66661784063, 83384.36355908474, 85323.15943881309, 85559.7016539988, 86141.5244289033, 0, 75058.98570238716, 76519.61400978893, 76708.83237106192, 78479.61731367245, 80306.46988436417, 81792.56177238707, 82188.66661784063, 83384.36355908474, 85323.15943881309, 85559.7016539988, 86141.5244289033, 0, 75058.98570238716, 76519.61400978893, 76708.83237106192, 78479.61731367245, 80306.46988436417, 81792.56177238707, 82188.66661784063, 83384.36355908474, 85323.15943881309, 85559.7016539988, 86141.5244289033, 0, 75058.98570238716, 76519.61400978893, 76708.83237106192, 78479.61731367245, 80306.46988436417, 81792.56177238707, 82188.66661784063, 83384.36355908474, 85323.15943881309, 85559.7016539988, 86141.5244289033, 0, 75058.98570238716, 76519.61400978893, 76708.83237106192, 78479.61731367245, 80306.46988436417, 81792.56177238707, 82188.66661784063, 83384.36355908474, 85323.15943881309, 85559.7016539988, 86141.5244289033], 60)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(60, 60)

np.array_equal(np_weights[0], np_weights[11])

True

np.array_equal(np_weights[0], np_weights[12])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:128.599272013
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.333760023
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.405138969
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.780799984932
Training with lmbda:78479.6173137, 4
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.780600011349
Training with lmbda:80306.4698844, 5
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:81792.5617724, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:82188.6666178, 7
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:85323.1594388, 9
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.788600027561
Training with lmbda:85559.701654, 10
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:115.57141614
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:125.12041688
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:121.365795851
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Training with lmbda:81792.5617724, 18
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0443650297821 and training accuracy:0.987364768982
validation cost:0.0492106229067 and validation accuracy:0.988051474094
Training on :(2, 3)
Time taken:123.889887094
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:115.910176039
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.728933096
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:121.07625103
Method 3 test accuracy:0.794099986553
Training with lmbda:82188.6666178, 19
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Valid features:(1088, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.124292135
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:125.266093016
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:121.618806124
Method 3 test accuracy:0.793399989605
Training with lmbda:83384.3635591, 20
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 24
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787899971008
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:122.854230881
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Training with lmbda:76519.6140098, 26
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787500023842
Training with lmbda:76708.8323711, 27
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:130.696455002
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:121.287006855
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:82188.6666178, 31
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:83384.3635591, 32
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 36
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.778999984264
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:81792.5617724, 54
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:83384.3635591, 56
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:85323.1594388, 57
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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validation cost:0.0208057481796 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0159669518471 and training accuracy:0.997654914856
validation cost:0.016457054764 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0137404799461 and training accuracy:0.998015701771
validation cost:0.014080952853 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0119921052828 and training accuracy:0.998196065426
validation cost:0.0127606615424 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0107437679544 and training accuracy:0.998466670513
validation cost:0.0114796431735 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.00958537403494 and training accuracy:0.998917639256
validation cost:0.00961663946509 and validation accuracy:0.9981752038
Training on :(6, 7)
Time taken:128.72305584
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151612833142 and training accuracy:0.967032968998
validation cost:0.14728243649 and validation accuracy:0.971751391888
Training on :(8, 9)
training cost:0.103492751718 and training accuracy:0.971689343452
validation cost:0.102921471 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0822907015681 and training accuracy:0.975973188877
validation cost:0.0817646235228 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.0691960677505 and training accuracy:0.980629563332
validation cost:0.0685686245561 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0609834827483 and training accuracy:0.982864618301
validation cost:0.0602100081742 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0539142228663 and training accuracy:0.984820246696
validation cost:0.0506231710315 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.04902433604 and training accuracy:0.986124038696
validation cost:0.0464851371944 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0448661670089 and training accuracy:0.987707197666
validation cost:0.0432286076248 and validation accuracy:0.992467045784
Training on :(8, 9)
training cost:0.0424690172076 and training accuracy:0.988079726696
validation cost:0.0415023565292 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:128.892805099
Method 3 test accuracy:0.778500020504
Total time:37096.9317429

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_11lmbdas_ar1_3lyrs_he1_75_875.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7811	75058.985702
2	0.7808	76519.614010
3	0.7808	76708.832371
4	0.7806	78479.617314
5	0.7808	80306.469884
6	0.7802	81792.561772
7	0.7805	82188.666618
8	0.7808	83384.363559
9	0.7886	85323.159439
10	0.7805	85559.701654
11	0.7806	86141.524429
12	0.7927	0.000000
13	0.7939	75058.985702
14	0.7936	76519.614010
15	0.7943	76708.832371
16	0.7937	78479.617314
17	0.7936	80306.469884
18	0.7941	81792.561772
19	0.7934	82188.666618
20	0.7936	83384.363559
21	0.7931	85323.159439
22	0.7933	85559.701654
23	0.7943	86141.524429
24	0.7879	0.000000
25	0.7868	75058.985702
26	0.7875	76519.614010
27	0.7874	76708.832371
28	0.7878	78479.617314
29	0.7870	80306.469884
30	0.7882	81792.561772
31	0.7877	82188.666618
32	0.7872	83384.363559
33	0.7876	85323.159439
34	0.7874	85559.701654
35	0.7877	86141.524429
36	0.7893	0.000000
37	0.7850	75058.985702
38	0.7904	76519.614010
39	0.7901	76708.832371
40	0.8039	78479.617314
41	0.7897	80306.469884
42	0.7971	81792.561772
43	0.7974	82188.666618
44	0.7973	83384.363559
45	0.7934	85323.159439
46	0.7970	85559.701654
47	0.7966	86141.524429
48	0.7784	0.000000
49	0.7793	75058.985702
50	0.7790	76519.614010
51	0.7790	76708.832371
52	0.7792	78479.617314
53	0.7793	80306.469884
54	0.7793	81792.561772
55	0.7788	82188.666618
56	0.7785	83384.363559
57	0.7786	85323.159439
58	0.7788	85559.701654
59	0.7785	86141.524429

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
mean_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
display(mean_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.78762
75058.985702	0.78522
76519.614010	0.78626
76708.832371	0.78632
78479.617314	0.78904
80306.469884	0.78608
81792.561772	0.78778
82188.666618	0.78756
83384.363559	0.78748
85323.159439	0.78826
85559.701654	0.78740
86141.524429	0.78754

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
std_acc_grouped_by_lmbda = acc_grouped_by_lmbda.std()
display(std_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.005442
75058.985702	0.005699
76519.614010	0.006226
76708.832371	0.006387
78479.617314	0.010151
80306.469884	0.006007
81792.561772	0.008005
82188.666618	0.008024
83384.363559	0.008050
85323.159439	0.005994
85559.701654	0.007883
86141.524429	0.008026

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
max_acc_grouped_by_lmbda = acc_grouped_by_lmbda.max()
display(max_acc_grouped_by_lmbda)

	Method3
lambdas
0.000000	0.7927
75058.985702	0.7939
76519.614010	0.7936
76708.832371	0.7943
78479.617314	0.8039
80306.469884	0.7936
81792.561772	0.7971
82188.666618	0.7974
83384.363559	0.7973
85323.159439	0.7934
85559.701654	0.7970
86141.524429	0.7966

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

mean_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

max_acc_grouped_by_lmbda.plot(y='Method3')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.show()

Init the writer with $\lambda$s (7.5, 8.0)

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_8lmbdas_ar1_3lyrs_he1_75_80', sess.graph)

Generate the $\lambda$s

np.random.seed(100)
n_lmbdas = 8
a = np.random.uniform(low=7.5, high=8.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 10
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[7.77170247 7.63918469 7.7122588  7.92238807 7.50235943 7.56078456
 7.83537454 7.91292638]
()
[75023.59428095 75607.84560392 76391.84692547 77122.58795375
 77717.02470895 78353.74542363 79129.26377553 79223.8806616 ]
()
([0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951, 0, 75023.59428095486, 75607.84560391557, 76391.84692546898, 77122.58795374566, 77717.02470895484, 78353.7454236339, 79129.26377552524, 79223.88066159951], 90)

Generate the random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(90, 90)

np.array_equal(np_weights[0], np_weights[8])

True

np.array_equal(np_weights[0], np_weights[9])

False

Commence the training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:136.535069942
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168302044272 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113371483982 and training accuracy:0.968548297882
validation cost:0.12098506093 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0885975807905 and training accuracy:0.97309333086
validation cost:0.0926486998796 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738820210099 and training accuracy:0.974093258381
validation cost:0.0787701904774 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0646886602044 and training accuracy:0.977183878422
validation cost:0.0672900676727 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0566079691052 and training accuracy:0.9806381464
validation cost:0.0583092048764 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0513964854181 and training accuracy:0.982819736004
validation cost:0.0509350299835 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0464820750058 and training accuracy:0.985546767712
validation cost:0.0469166785479 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427470132709 and training accuracy:0.987273871899
validation cost:0.0414676591754 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:124.113954067
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0990518555045 and training accuracy:0.991609752178
validation cost:0.0925189256668 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0539999529719 and training accuracy:0.99287801981
validation cost:0.0477138087153 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0376890674233 and training accuracy:0.994829297066
validation cost:0.0302194636315 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0290481522679 and training accuracy:0.99658536911
validation cost:0.0220831781626 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023657489568 and training accuracy:0.997756123543
validation cost:0.0176057368517 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0198712404817 and training accuracy:0.998341441154
validation cost:0.0145276719704 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0169922467321 and training accuracy:0.998341441154
validation cost:0.0122214574367 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0153050273657 and training accuracy:0.998146355152
validation cost:0.011213125661 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0139560960233 and training accuracy:0.998243927956
validation cost:0.0100094126537 and validation accuracy:1.0
Training on :(4, 5)
Time taken:114.010300875
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0636208951473 and training accuracy:0.991611778736
validation cost:0.0635736957192 and validation accuracy:0.989051103592
Training on :(6, 7)
training cost:0.0342947021127 and training accuracy:0.996843159199
validation cost:0.0337495431304 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0241673067212 and training accuracy:0.997745096684
validation cost:0.0247216559947 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0191191416234 and training accuracy:0.998015701771
validation cost:0.01931928657 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0155691420659 and training accuracy:0.998286306858
validation cost:0.0159959737211 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0129639329389 and training accuracy:0.9987372756
validation cost:0.0133697763085 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.011112768203 and training accuracy:0.998827457428
validation cost:0.0117992609739 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00979762617499 and training accuracy:0.999007821083
validation cost:0.0101021369919 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00877885892987 and training accuracy:0.999098062515
validation cost:0.00852270238101 and validation accuracy:0.999087572098
Training on :(6, 7)
Time taken:123.783849001
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151477068663 and training accuracy:0.965170443058
validation cost:0.148457437754 and validation accuracy:0.964218437672
Training on :(8, 9)
training cost:0.103641562164 and training accuracy:0.972527444363
validation cost:0.103159971535 and validation accuracy:0.973634660244
Training on :(8, 9)
training cost:0.082123234868 and training accuracy:0.976066291332
validation cost:0.0786714181304 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.069301366806 and training accuracy:0.979791402817
validation cost:0.0627456903458 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0595998130739 and training accuracy:0.982957720757
validation cost:0.0547399930656 and validation accuracy:0.987758934498
Training on :(8, 9)
training cost:0.0535054244101 and training accuracy:0.985285878181
validation cost:0.0488348640501 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0479301735759 and training accuracy:0.986775934696
validation cost:0.0455383919179 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.0442771986127 and training accuracy:0.987520933151
validation cost:0.0432717837393 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0408748500049 and training accuracy:0.988359093666
validation cost:0.0389142967761 and validation accuracy:0.993408679962
Training on :(8, 9)
Time taken:119.87639308
Method 3 test accuracy:0.78979998827
Training with lmbda:75023.594281, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
validation cost:0.0140941208228 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0115019194782 and training accuracy:0.997657477856
validation cost:0.0115101812407 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0099402749911 and training accuracy:0.997744202614
validation cost:0.00971961114556 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00863864738494 and training accuracy:0.998004496098
validation cost:0.0086479568854 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00776934204623 and training accuracy:0.99809128046
validation cost:0.0084388460964 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.00688597885892 and training accuracy:0.998178005219
validation cost:0.00751441437751 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:128.904242992
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.168326407671 and training accuracy:0.950004518032
validation cost:0.169079318643 and validation accuracy:0.943014681339
Training on :(2, 3)
training cost:0.113436385989 and training accuracy:0.968457400799
validation cost:0.120995566249 and validation accuracy:0.962316155434
Training on :(2, 3)
training cost:0.0886830016971 and training accuracy:0.973184227943
validation cost:0.0928283855319 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0738756507635 and training accuracy:0.974093258381
validation cost:0.0789003744721 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0645552128553 and training accuracy:0.977456569672
validation cost:0.0673339515924 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.0565150380135 and training accuracy:0.980729043484
validation cost:0.0583194643259 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0511750020087 and training accuracy:0.982819736004
validation cost:0.0505346208811 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0465326309204 and training accuracy:0.985455870628
validation cost:0.0466939024627 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0427991561592 and training accuracy:0.987182974815
validation cost:0.0416137315333 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:123.345343113
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.0989966988564 and training accuracy:0.991609752178
validation cost:0.0915736556053 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0542582646012 and training accuracy:0.992780506611
validation cost:0.0479513183236 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0378987528384 and training accuracy:0.994634151459
validation cost:0.0303465798497 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0292774755508 and training accuracy:0.99658536911
validation cost:0.0225297454745 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.023761132732 and training accuracy:0.997756123543
validation cost:0.0178401097655 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0201623681933 and training accuracy:0.998341441154
validation cost:0.0148836476728 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0172377955168 and training accuracy:0.998439013958
validation cost:0.0126786977053 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0156271532178 and training accuracy:0.998146355152
validation cost:0.0114567382261 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0141885150224 and training accuracy:0.998048782349
validation cost:0.0103687616065 and validation accuracy:1.0
Training on :(4, 5)
Time taken:114.677459002
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0639498829842 and training accuracy:0.991250991821
validation cost:0.0634320303798 and validation accuracy:0.98813867569
Training on :(6, 7)
training cost:0.0343152657151 and training accuracy:0.997203946114
validation cost:0.0344460904598 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.024252442643 and training accuracy:0.997835278511
validation cost:0.0248887445778 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0189607832581 and training accuracy:0.998015701771
validation cost:0.019478680566 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0156978704035 and training accuracy:0.998196065426
validation cost:0.0163251813501 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0131867853925 and training accuracy:0.9987372756
validation cost:0.0132689010352 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0114397937432 and training accuracy:0.998647093773
validation cost:0.0117318052799 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0100808767602 and training accuracy:0.998917639256
validation cost:0.0104270121083 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.00906547438353 and training accuracy:0.999098062515
validation cost:0.00887079443783 and validation accuracy:0.999087572098
Training on :(6, 7)
Time taken:123.800060987
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.153863146901 and training accuracy:0.964332282543
validation cost:0.149105384946 and validation accuracy:0.964218437672
Training on :(8, 9)
training cost:0.103828720748 and training accuracy:0.972154974937
validation cost:0.100453525782 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0825904533267 and training accuracy:0.975507557392
validation cost:0.0805253982544 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0690082907677 and training accuracy:0.979791402817
validation cost:0.0640916079283 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.060409065336 and training accuracy:0.983330249786
validation cost:0.0557250007987 and validation accuracy:0.989642202854
Training on :(8, 9)
training cost:0.0540052577853 and training accuracy:0.985006511211
validation cost:0.0500498972833 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0484573952854 and training accuracy:0.986682832241
validation cost:0.047080270946 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0449270531535 and training accuracy:0.987707197666
validation cost:0.043886680156 and validation accuracy:0.991525411606
Training on :(8, 9)
training cost:0.041299328208 and training accuracy:0.988452196121
validation cost:0.0400593131781 and validation accuracy:0.991525411606
Training on :(8, 9)
Time taken:120.082966089
Method 3 test accuracy:0.781099975109
Training with lmbda:75607.8456039, 2
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0424780659378 and training accuracy:0.99514144659
validation cost:0.0425861291587 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0238319151103 and training accuracy:0.995575249195
validation cost:0.0244052931666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0170864723623 and training accuracy:0.996703088284
validation cost:0.0173231437802 and validation accuracy:0.996488153934
Training on :(0, 1)
training cost:0.0137033909559 and training accuracy:0.997136890888
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:77717.024709, 5
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78353.7454236, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:79129.2637755, 7
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75607.8456039, 11
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:76391.8469255, 12
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.684590101
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 18
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75023.594281, 19
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75607.8456039, 20
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.420145035
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787000000477
Training with lmbda:76391.8469255, 21
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:123.974123955
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.316118002
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787599980831
Training with lmbda:77717.024709, 23
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.787100017071
Training with lmbda:78353.7454236, 24
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.820515156
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75023.594281, 28
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78353.7454236, 33
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 36
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.822031021
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75607.8456039, 38
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:76391.8469255, 39
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.306868076
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:121.000211
Method 3 test accuracy:0.778900027275
Training with lmbda:79129.2637755, 43
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.778599977493
Training with lmbda:79223.8806616, 44
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
training cost:0.00698435213417 and training accuracy:0.998004496098
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:79223.8806616, 53
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:125.025063038
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75023.594281, 64
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.947489023
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75023.594281, 82
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.777700006962
Training with lmbda:75607.8456039, 83
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.461756945
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78353.7454236, 87
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.546977997
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:79129.2637755, 88
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:133.939596176
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.15157084167 and training accuracy:0.962935388088
validation cost:0.155805915594 and validation accuracy:0.95951038599
Training on :(8, 9)
training cost:0.105585612357 and training accuracy:0.970571815968
validation cost:0.108802393079 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0854640677571 and training accuracy:0.973831236362
validation cost:0.0898375287652 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0732871815562 and training accuracy:0.976811349392
validation cost:0.0763674080372 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.063368037343 and training accuracy:0.981002032757
validation cost:0.0647814944386 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0561137497425 and training accuracy:0.983050823212
validation cost:0.0564585626125 and validation accuracy:0.98681730032
Training on :(8, 9)
training cost:0.0512743219733 and training accuracy:0.985099673271
validation cost:0.052012886852 and validation accuracy:0.989642202854
Training on :(8, 9)
training cost:0.045894600451 and training accuracy:0.986217200756
validation cost:0.0465811118484 and validation accuracy:0.990583777428
Training on :(8, 9)
training cost:0.0429239273071 and training accuracy:0.986869037151
validation cost:0.0428730882704 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:128.891454935
Method 3 test accuracy:0.777599990368
Training with lmbda:79223.8806616, 89
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.0417908243835 and training accuracy:0.994967877865
validation cost:0.0471030026674 and validation accuracy:0.992976307869
Training on :(0, 1)
training cost:0.0232260320336 and training accuracy:0.995228171349
validation cost:0.0289236549288 and validation accuracy:0.992098331451
Training on :(0, 1)
training cost:0.0164824090898 and training accuracy:0.997310400009
validation cost:0.0200726669282 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.0131519054994 and training accuracy:0.997830986977
validation cost:0.0164472255856 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.0110759427771 and training accuracy:0.997744202614
validation cost:0.01487235073 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00949898548424 and training accuracy:0.998004496098
validation cost:0.0133176892996 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00843800976872 and training accuracy:0.99809128046
validation cost:0.011507817544 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00766462180763 and training accuracy:0.998351573944
validation cost:0.0114531647414 and validation accuracy:0.995610177517
Training on :(0, 1)
training cost:0.00702045299113 and training accuracy:0.998351573944
validation cost:0.0103198196739 and validation accuracy:0.995610177517
Training on :(0, 1)
Time taken:141.118446112
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.162940382957 and training accuracy:0.952822446823
validation cost:0.166034370661 and validation accuracy:0.950367629528
Training on :(2, 3)
training cost:0.108155660331 and training accuracy:0.970275402069
validation cost:0.111423708498 and validation accuracy:0.963235318661
Training on :(2, 3)
training cost:0.0843611061573 and training accuracy:0.973002433777
validation cost:0.0880932807922 and validation accuracy:0.965992629528
Training on :(2, 3)
training cost:0.0718272700906 and training accuracy:0.976093053818
validation cost:0.0758925527334 and validation accuracy:0.974264681339
Training on :(2, 3)
training cost:0.0622203834355 and training accuracy:0.980365395546
validation cost:0.0654985383153 and validation accuracy:0.977941155434
Training on :(2, 3)
training cost:0.054221406579 and training accuracy:0.983819663525
validation cost:0.0570843294263 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0490778125823 and training accuracy:0.985637664795
validation cost:0.0533064045012 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0453459732234 and training accuracy:0.986274003983
validation cost:0.0490844845772 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.0418931357563 and training accuracy:0.987546563148
validation cost:0.0432323478162 and validation accuracy:0.985294103622
Training on :(2, 3)
Time taken:132.76019311
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.10091740638 and training accuracy:0.991512179375
validation cost:0.093572370708 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0563026033342 and training accuracy:0.993073165417
validation cost:0.049197267741 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0387045815587 and training accuracy:0.995707333088
validation cost:0.0315217785537 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0302623286843 and training accuracy:0.99658536911
validation cost:0.0238622426987 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0252375006676 and training accuracy:0.996780514717
validation cost:0.019278222695 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0213981866837 and training accuracy:0.996975600719
validation cost:0.0154308229685 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0186043027788 and training accuracy:0.99726831913
validation cost:0.0136905191466 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0167006868869 and training accuracy:0.99726831913
validation cost:0.01181945391 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0150844575837 and training accuracy:0.997463405132
validation cost:0.010355421342 and validation accuracy:1.0
Training on :(4, 5)
Time taken:124.780086994
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.0634964108467 and training accuracy:0.991160809994
validation cost:0.0622617974877 and validation accuracy:0.989963531494
Training on :(6, 7)
training cost:0.034435685724 and training accuracy:0.996482372284
validation cost:0.0325755365193 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0245854742825 and training accuracy:0.997384309769
validation cost:0.0228094514459 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0188301242888 and training accuracy:0.997654914856
validation cost:0.0168310068548 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0153751233593 and training accuracy:0.998105883598
validation cost:0.0138392047957 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0131724188104 and training accuracy:0.998376488686
validation cost:0.0118307983503 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0112944040447 and training accuracy:0.998827457428
validation cost:0.0102443601936 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0100962286815 and training accuracy:0.998917639256
validation cost:0.00916360504925 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.00915245898068 and training accuracy:0.999007821083
validation cost:0.00824708770961 and validation accuracy:1.0
Training on :(6, 7)
Time taken:134.450176954
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.151649415493 and training accuracy:0.962842226028
validation cost:0.155602201819 and validation accuracy:0.960451960564
Training on :(8, 9)
training cost:0.105758495629 and training accuracy:0.970664918423
validation cost:0.109275273979 and validation accuracy:0.977401137352
Training on :(8, 9)
training cost:0.0852840095758 and training accuracy:0.974110662937
validation cost:0.0890263020992 and validation accuracy:0.977401137352
Training on :(8, 9)
training cost:0.0732069611549 and training accuracy:0.976811349392
validation cost:0.0762141570449 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.0632278546691 and training accuracy:0.980908930302
validation cost:0.0645297393203 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.055744715035 and training accuracy:0.983330249786
validation cost:0.0570819154382 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0509763471782 and training accuracy:0.985285878181
validation cost:0.0517531298101 and validation accuracy:0.989642202854
Training on :(8, 9)
training cost:0.0464550517499 and training accuracy:0.986030936241
validation cost:0.0471315048635 and validation accuracy:0.989642202854
Training on :(8, 9)
training cost:0.0430245101452 and training accuracy:0.986962199211
validation cost:0.0427758395672 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:131.264486074
Method 3 test accuracy:0.779600024223
Total time:55639.4809101

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_11lmbdas_ar1_3lyrs_he1_75_80.csv')
final_test_acc

	Method3	lambdas
0	0.7898	0.000000
1	0.7811	75023.594281
2	0.7809	75607.845604
3	0.7813	76391.846925
4	0.7812	77122.587954
5	0.7807	77717.024709
6	0.7810	78353.745424
7	0.7814	79129.263776
8	0.7803	79223.880662
9	0.7927	0.000000
10	0.7946	75023.594281
11	0.7937	75607.845604
12	0.7940	76391.846925
13	0.7940	77122.587954
14	0.7941	77717.024709
15	0.7945	78353.745424
16	0.7935	79129.263776
17	0.7947	79223.880662
18	0.7879	0.000000
19	0.7878	75023.594281
20	0.7870	75607.845604
21	0.7880	76391.846925
22	0.7876	77122.587954
23	0.7871	77717.024709
24	0.7877	78353.745424
25	0.7874	79129.263776
26	0.7863	79223.880662
27	0.7893	0.000000
28	0.7897	75023.594281
29	0.7849	75607.845604
...	...	...
60	0.8009	78353.745424
61	0.7984	79129.263776
62	0.7979	79223.880662
63	0.7973	0.000000
64	0.7967	75023.594281
65	0.7966	75607.845604
66	0.8016	76391.846925
67	0.7940	77122.587954
68	0.7954	77717.024709
69	0.7949	78353.745424
70	0.7940	79129.263776
71	0.7948	79223.880662
72	0.8015	0.000000
73	0.7927	75023.594281
74	0.7925	75607.845604
75	0.8028	76391.846925
76	0.7918	77122.587954
77	0.7926	77717.024709
78	0.7923	78353.745424
79	0.7925	79129.263776
80	0.7923	79223.880662
81	0.7759	0.000000
82	0.7777	75023.594281
83	0.7769	75607.845604
84	0.7782	76391.846925
85	0.7777	77122.587954
86	0.7775	77717.024709
87	0.7769	78353.745424
88	0.7776	79129.263776
89	0.7796	79223.880662

90 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
final_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
final_acc_grouped_by_lmbda['S.D'] = acc_grouped_by_lmbda.std()
final_acc_grouped_by_lmbda['MIN'] = acc_grouped_by_lmbda.min()
final_acc_grouped_by_lmbda['MAX'] = acc_grouped_by_lmbda.max()
final_acc_grouped_by_lmbda['MED'] = acc_grouped_by_lmbda.median()
final_acc_grouped_by_lmbda.reset_index(inplace=True)
final_acc_grouped_by_lmbda

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.78983	0.008506	0.7759	0.8015	0.78955
1	75023.594281	0.78809	0.007356	0.7777	0.7977	0.78875
2	75607.845604	0.78774	0.007806	0.7769	0.8005	0.78595
3	76391.846925	0.78976	0.009035	0.7782	0.8028	0.78925
4	77122.587954	0.78799	0.007161	0.7777	0.7987	0.78965
5	77717.024709	0.78782	0.007237	0.7775	0.7980	0.78835
6	78353.745424	0.78838	0.007835	0.7769	0.8009	0.78975
7	79129.263776	0.78861	0.007618	0.7776	0.7984	0.78995
8	79223.880662	0.78868	0.007626	0.7785	0.7979	0.78930

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_acc_grouped_by_lmbda.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (7.5, 10.0) non-spk classification

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_14lmbdas_ar1_3lyrs_he1_75_10-non_spk', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 14
a = np.random.uniform(low=7.5, high=10.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 10
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[8.85851235 8.19592346 8.56129398 9.61194033 7.51179714 7.8039228
 9.17687271 9.56463189 7.84176647 8.93773332 9.72830489 8.02300531
 7.96332055 7.77094223]
()
[75117.97140477 77709.42226161 78039.22801958 78417.66474212
 79633.20548875 80230.05305293 81959.23462734 85612.93976873
 88585.12354477 89377.33323568 91768.72711817 95646.31887763
 96119.403308   97283.04885781]
()
([0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659, 0, 75117.9714047743, 77709.42226160638, 78039.22801957786, 78417.66474212382, 79633.20548875188, 80230.05305292974, 81959.23462734491, 85612.93976872832, 88585.12354477413, 89377.33323568125, 91768.72711816947, 95646.3188776262, 96119.40330799759, 97283.04885780659], 150)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(150, 150)

np.array_equal(np_weights[0], np_weights[14])

True

np.array_equal(np_weights[0], np_weights[15])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:134.818016052
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.360579758883 and training accuracy:0.934915006161
validation cost:0.366988688707 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.176190719008 and training accuracy:0.958094716072
validation cost:0.182327464223 and validation accuracy:0.954044103622
Training on :(2, 3)
training cost:0.120868973434 and training accuracy:0.969093739986
validation cost:0.127899214625 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.0940565243363 and training accuracy:0.975456774235
validation cost:0.10124284029 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0779117867351 and training accuracy:0.978456497192
validation cost:0.0847291350365 and validation accuracy:0.974264681339
Training on :(2, 3)
training cost:0.0669855996966 and training accuracy:0.981819808483
validation cost:0.0732256993651 and validation accuracy:0.977941155434
Training on :(2, 3)
training cost:0.0590222999454 and training accuracy:0.983456075191
validation cost:0.0646186545491 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0529175139964 and training accuracy:0.985183179379
validation cost:0.0578845217824 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.04806323722 and training accuracy:0.986364901066
validation cost:0.0524483658373 and validation accuracy:0.983455896378
Training on :(2, 3)
Time taken:130.100168943
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.217629268765 and training accuracy:0.97921949625
validation cost:0.218148618937 and validation accuracy:0.985192477703
Training on :(4, 5)
training cost:0.0974639952183 and training accuracy:0.990341484547
validation cost:0.0916447117925 and validation accuracy:0.995064139366
Training on :(4, 5)
training cost:0.0610082633793 and training accuracy:0.994146347046
validation cost:0.0536370389163 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0443231239915 and training accuracy:0.99590241909
validation cost:0.0367065370083 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0349110253155 and training accuracy:0.996195137501
validation cost:0.0274240188301 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0288931559771 and training accuracy:0.996390223503
validation cost:0.0216537415981 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0247139781713 and training accuracy:0.996487796307
validation cost:0.0177568681538 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0216373112053 and training accuracy:0.996682941914
validation cost:0.0149661740288 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.019272049889 and training accuracy:0.997073173523
validation cost:0.0128794498742 and validation accuracy:1.0
Training on :(4, 5)
Time taken:119.067508936
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.151656508446 and training accuracy:0.98737257719
validation cost:0.145524710417 and validation accuracy:0.98631387949
Training on :(6, 7)
training cost:0.0638237595558 and training accuracy:0.993325531483
validation cost:0.0611358545721 and validation accuracy:0.992700755596
Training on :(6, 7)
training cost:0.0398089848459 and training accuracy:0.995850980282
validation cost:0.0380516797304 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0289002507925 and training accuracy:0.996933341026
validation cost:0.0274686124176 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0226961262524 and training accuracy:0.997654914856
validation cost:0.0213998220861 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0186950284988 and training accuracy:0.998015701771
validation cost:0.0174691136926 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0158997606486 and training accuracy:0.998286306858
validation cost:0.014717518352 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0138351758942 and training accuracy:0.998466670513
validation cost:0.0126881599426 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0122469142079 and training accuracy:0.998827457428
validation cost:0.0111321751028 and validation accuracy:1.0
Training on :(6, 7)
Time taken:123.717694998
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.217926025391 and training accuracy:0.94952505827
validation cost:0.220475539565 and validation accuracy:0.944444417953
Training on :(8, 9)
training cost:0.136503621936 and training accuracy:0.963028490543
validation cost:0.139507696033 and validation accuracy:0.958568751812
Training on :(8, 9)
training cost:0.104578927159 and training accuracy:0.969361126423
validation cost:0.108049310744 and validation accuracy:0.967043340206
Training on :(8, 9)
training cost:0.0861355289817 and training accuracy:0.974296867847
validation cost:0.0895406752825 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.0736218318343 and training accuracy:0.978301346302
validation cost:0.0766408592463 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0644264519215 and training accuracy:0.980350136757
validation cost:0.0669165104628 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.0573468096554 and training accuracy:0.983050823212
validation cost:0.0592649653554 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0517177283764 and training accuracy:0.985006511211
validation cost:0.0530807264149 and validation accuracy:0.988700568676
Training on :(8, 9)
training cost:0.0471327267587 and training accuracy:0.986496567726
validation cost:0.047990180552 and validation accuracy:0.990583777428
Training on :(8, 9)
Time taken:117.707244873
Method 3 test accuracy:0.729499995708
Training with lmbda:75117.9714048, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:79633.2054888, 5
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:80230.0530529, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:112.092031956
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:88585.1235448, 9
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0503821931779 and training accuracy:0.986364901066
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Training on :(2, 3)
Time taken:120.206701994
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.810699999332
Training with lmbda:89377.3332357, 10
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Train features:(11001, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:120.719032049
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0536427982152 and training accuracy:0.985751509666
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Training on :(8, 9)
Time taken:117.06744194
Method 3 test accuracy:0.805000007153
Training with lmbda:91768.7271182, 11
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 15
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.851557016
Method 3 test accuracy:0.718800008297
Training with lmbda:75117.9714048, 16
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:80230.0530529, 21
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:89377.3332357, 25
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91768.7271182, 26
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 30
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.448055983
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Training with lmbda:75117.9714048, 31
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:80230.0530529, 36
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.766399979591
Training with lmbda:89377.3332357, 40
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0171578396112 and training accuracy:0.999188244343
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.060328007
Method 3 test accuracy:0.766799986362
Training with lmbda:91768.7271182, 41
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 45
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.116851091
Method 3 test accuracy:0.726400017738
Training with lmbda:75117.9714048, 46
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.788299977779
Training with lmbda:79633.2054888, 50
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.23606205
Method 3 test accuracy:0.787999987602
Training with lmbda:80230.0530529, 51
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:89377.3332357, 55
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.556089163
Method 3 test accuracy:0.791199982166
Training with lmbda:91768.7271182, 56
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:112.518367052
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:97283.0488578, 59
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:119.631369114
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:116.898204803
Method 3 test accuracy:0.787100017071
Training with lmbda:0, 60
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0126600628719 and training accuracy:0.998556852341
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Training on :(6, 7)
Time taken:120.536652088
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0478190034628 and training accuracy:0.986124038696
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Training on :(8, 9)
Time taken:117.40675807
Method 3 test accuracy:0.717700004578
Training with lmbda:75117.9714048, 61
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:111.949266195
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78417.6647421, 64
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.771799981594
Training with lmbda:79633.2054888, 65
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:120.897231102
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.16404891
Method 3 test accuracy:0.772300004959
Training with lmbda:80230.0530529, 66
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:89377.3332357, 70
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.340358973
Method 3 test accuracy:0.77380001545
Training with lmbda:91768.7271182, 71
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 75
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:75117.9714048, 76
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:89377.3332357, 85
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.323856115
Method 3 test accuracy:0.78719997406
Training with lmbda:91768.7271182, 86
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 90
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.723900020123
Training with lmbda:75117.9714048, 91
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:91768.7271182, 101
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:112.023706913
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:97283.0488578, 104
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0487624891102 and training accuracy:0.987637460232
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Training on :(2, 3)
Time taken:119.948111057
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.372467995
Method 3 test accuracy:0.808499991894
Training with lmbda:0, 105
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0189895760268 and training accuracy:0.997560977936
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:120.687777042
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0483115538955 and training accuracy:0.986124038696
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Training on :(8, 9)
Time taken:117.586513042
Method 3 test accuracy:0.709200024605
Training with lmbda:75117.9714048, 106
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Repeat:0
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0501283146441 and training accuracy:0.986546695232
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Training on :(2, 3)
Time taken:119.770702839
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0265055913478 and training accuracy:0.997170746326
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0168532319367 and training accuracy:0.999368607998
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Training on :(6, 7)
Time taken:121.004407883
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.302399874
Method 3 test accuracy:0.759599983692
Training with lmbda:77709.4222616, 107
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
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Valid features:(1088, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:111.973500967
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:121.132866144
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:118.056609869
Method 3 test accuracy:0.760800004005
Training with lmbda:78039.2280196, 108
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.050187587738 and training accuracy:0.986546695232
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Training on :(2, 3)
Time taken:119.814682961
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:78417.6647421, 109
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.194795132
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Train features:(11087, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.761099994183
Training with lmbda:79633.2054888, 110
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:120.981385946
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.76139998436
Training with lmbda:81959.2346273, 112
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:88585.1235448, 114
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:89377.3332357, 115
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:120.823318005
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.764599978924
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0505381375551 and training accuracy:0.986546695232
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0168109741062 and training accuracy:0.998917639256
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.815800011158
Training with lmbda:77709.4222616, 122
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.817099988461
Training with lmbda:78039.2280196, 123
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0495509691536 and training accuracy:0.986637592316
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Training on :(2, 3)
Time taken:119.931032181
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:81959.2346273, 127
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.316025019
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.81970000267
Training with lmbda:89377.3332357, 130
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0173125248402 and training accuracy:0.998917639256
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Training on :(6, 7)
Time taken:120.997171879
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 135
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:81959.2346273, 142
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0603910982609 and training accuracy:0.984819591045
validation cost:0.0632961094379 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0544275976717 and training accuracy:0.986274003983
validation cost:0.056925162673 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.049673717469 and training accuracy:0.987637460232
validation cost:0.0517920553684 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:125.438028097
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.236842438579 and training accuracy:0.980292677879
validation cost:0.239309713244 and validation accuracy:0.985192477703
Training on :(4, 5)
training cost:0.110984303057 and training accuracy:0.989853680134
validation cost:0.106901414692 and validation accuracy:0.994077026844
Training on :(4, 5)
training cost:0.0727309659123 and training accuracy:0.993951201439
validation cost:0.066779717803 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.054911095649 and training accuracy:0.995024383068
validation cost:0.0484515205026 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0446573346853 and training accuracy:0.995414614677
validation cost:0.0381312482059 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0379739291966 and training accuracy:0.996097564697
validation cost:0.0315424278378 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.033250387758 and training accuracy:0.996292710304
validation cost:0.0269764270633 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0297184009105 and training accuracy:0.99658536911
validation cost:0.0236259419471 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0269660707563 and training accuracy:0.997170746326
validation cost:0.021060872823 and validation accuracy:1.0
Training on :(4, 5)
Time taken:121.357002974
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.160160392523 and training accuracy:0.991431415081
validation cost:0.153138846159 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0707712396979 and training accuracy:0.995670616627
validation cost:0.067348189652 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0464226379991 and training accuracy:0.997203946114
validation cost:0.0440162606537 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0352779142559 and training accuracy:0.997745096684
validation cost:0.033265132457 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0288677290082 and training accuracy:0.998286306858
validation cost:0.0270510427654 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0246789492667 and training accuracy:0.998647093773
validation cost:0.0229823924601 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0217098034918 and training accuracy:0.9987372756
validation cost:0.0200980249792 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0194845441729 and training accuracy:0.998827457428
validation cost:0.0179396793246 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0177472662181 and training accuracy:0.998827457428
validation cost:0.0162594933063 and validation accuracy:1.0
Training on :(6, 7)
Time taken:132.92354393
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.222079575062 and training accuracy:0.956137061119
validation cost:0.224460929632 and validation accuracy:0.948210895061
Training on :(8, 9)
training cost:0.137207388878 and training accuracy:0.964984178543
validation cost:0.140238374472 and validation accuracy:0.96516007185
Training on :(8, 9)
training cost:0.106464833021 and training accuracy:0.971223711967
validation cost:0.109690360725 and validation accuracy:0.972693026066
Training on :(8, 9)
training cost:0.0893251374364 and training accuracy:0.975321292877
validation cost:0.0923881307244 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0779189765453 and training accuracy:0.978115081787
validation cost:0.0806563273072 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.0696142762899 and training accuracy:0.980443298817
validation cost:0.0719729363918 and validation accuracy:0.983050823212
Training on :(8, 9)
training cost:0.0632329583168 and training accuracy:0.982305824757
validation cost:0.0652115494013 and validation accuracy:0.984934091568
Training on :(8, 9)
training cost:0.0581506341696 and training accuracy:0.983795881271
validation cost:0.0597777292132 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0539921224117 and training accuracy:0.985285878181
validation cost:0.0553047172725 and validation accuracy:0.987758934498
Training on :(8, 9)
Time taken:127.242937803
Method 3 test accuracy:0.758700013161
Training with lmbda:97283.0488578, 149
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.203907415271 and training accuracy:0.997570693493
validation cost:0.201984629035 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0566555894911 and training accuracy:0.99809128046
validation cost:0.0579187460244 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0322347804904 and training accuracy:0.998351573944
validation cost:0.0339787490666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0228093471378 and training accuracy:0.998525083065
validation cost:0.0246704109013 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0178289748728 and training accuracy:0.998525083065
validation cost:0.0197088513523 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0147348884493 and training accuracy:0.998698592186
validation cost:0.0165966041386 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126142920926 and training accuracy:0.998698592186
validation cost:0.0144430585206 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.011062421836 and training accuracy:0.998872101307
validation cost:0.0128502687439 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00987247936428 and training accuracy:0.99895888567
validation cost:0.0116164442152 and validation accuracy:0.997366130352
Training on :(0, 1)
Time taken:143.876137018
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.364260882139 and training accuracy:0.940914452076
validation cost:0.368607312441 and validation accuracy:0.944852948189
Training on :(2, 3)
training cost:0.176007464528 and training accuracy:0.960730850697
validation cost:0.179690614343 and validation accuracy:0.957720577717
Training on :(2, 3)
training cost:0.120924897492 and training accuracy:0.971366226673
validation cost:0.124957405031 and validation accuracy:0.967830896378
Training on :(2, 3)
training cost:0.0945963561535 and training accuracy:0.975184082985
validation cost:0.0986141562462 and validation accuracy:0.970588207245
Training on :(2, 3)
training cost:0.0788337662816 and training accuracy:0.980001807213
validation cost:0.0825601294637 and validation accuracy:0.978860318661
Training on :(2, 3)
training cost:0.0681786239147 and training accuracy:0.982728838921
validation cost:0.0715033859015 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.0604105778039 and training accuracy:0.984819591045
validation cost:0.0633140131831 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0544465221465 and training accuracy:0.986274003983
validation cost:0.0569427534938 and validation accuracy:0.984375
Training on :(2, 3)
training cost:0.0496923103929 and training accuracy:0.987637460232
validation cost:0.0518095903099 and validation accuracy:0.987132370472
Training on :(2, 3)
Time taken:127.151309013
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.236995860934 and training accuracy:0.980292677879
validation cost:0.239468246698 and validation accuracy:0.985192477703
Training on :(4, 5)
training cost:0.111092835665 and training accuracy:0.989853680134
validation cost:0.10701469332 and validation accuracy:0.994077026844
Training on :(4, 5)
training cost:0.0728179514408 and training accuracy:0.993951201439
validation cost:0.0668704286218 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0549845770001 and training accuracy:0.995024383068
validation cost:0.0485279411077 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.044721595943 and training accuracy:0.995414614677
validation cost:0.038197863847 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0380314141512 and training accuracy:0.996097564697
validation cost:0.0316017307341 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0333021916449 and training accuracy:0.996292710304
validation cost:0.027029691264 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0297655649483 and training accuracy:0.996682941914
validation cost:0.0236742515117 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0270097125322 and training accuracy:0.997170746326
validation cost:0.0211053919047 and validation accuracy:1.0
Training on :(4, 5)
Time taken:120.229645014
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.160269021988 and training accuracy:0.991431415081
validation cost:0.15324446559 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0708465278149 and training accuracy:0.995670616627
validation cost:0.0674203410745 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0464867725968 and training accuracy:0.997203946114
validation cost:0.0440776720643 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0353352278471 and training accuracy:0.997745096684
validation cost:0.0333201810718 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0289199352264 and training accuracy:0.998286306858
validation cost:0.0271013639867 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0247270632535 and training accuracy:0.998647093773
validation cost:0.0230289194733 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0217546410859 and training accuracy:0.9987372756
validation cost:0.0201414357871 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0195266827941 and training accuracy:0.998827457428
validation cost:0.017980504781 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.017786944285 and training accuracy:0.998827457428
validation cost:0.016297949478 and validation accuracy:1.0
Training on :(6, 7)
Time taken:140.783217907
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.222183570266 and training accuracy:0.956137061119
validation cost:0.224563091993 and validation accuracy:0.948210895061
Training on :(8, 9)
training cost:0.137267515063 and training accuracy:0.964984178543
validation cost:0.140296772122 and validation accuracy:0.96516007185
Training on :(8, 9)
training cost:0.106519706547 and training accuracy:0.971223711967
validation cost:0.109743215144 and validation accuracy:0.972693026066
Training on :(8, 9)
training cost:0.0893808379769 and training accuracy:0.975321292877
validation cost:0.0924418196082 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0779767930508 and training accuracy:0.978115081787
validation cost:0.0807129666209 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.069674089551 and training accuracy:0.980443298817
validation cost:0.0720321163535 and validation accuracy:0.983050823212
Training on :(8, 9)
training cost:0.0632944405079 and training accuracy:0.982305824757
validation cost:0.065273463726 and validation accuracy:0.984934091568
Training on :(8, 9)
training cost:0.0582133978605 and training accuracy:0.983795881271
validation cost:0.0598418228328 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0540557429194 and training accuracy:0.985379040241
validation cost:0.0553705245256 and validation accuracy:0.987758934498
Training on :(8, 9)
Time taken:132.073575974
Method 3 test accuracy:0.759000003338
Total time:90175.8174529

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_75_10_non_spike_claasify.csv')
final_test_acc

	Method3	lambdas
0	0.7295	0.000000
1	0.8091	75117.971405
2	0.8088	77709.422262
3	0.8087	78039.228020
4	0.8086	78417.664742
5	0.8084	79633.205489
6	0.8087	80230.053053
7	0.8090	81959.234627
8	0.8095	85612.939769
9	0.8107	88585.123545
10	0.8050	89377.333236
11	0.8054	91768.727118
12	0.8060	95646.318878
13	0.8064	96119.403308
14	0.8065	97283.048858
15	0.7188	0.000000
16	0.7694	75117.971405
17	0.7701	77709.422262
18	0.7701	78039.228020
19	0.7700	78417.664742
20	0.7702	79633.205489
21	0.7703	80230.053053
22	0.7705	81959.234627
23	0.7785	85612.939769
24	0.7786	88585.123545
25	0.7790	89377.333236
26	0.7794	91768.727118
27	0.7811	95646.318878
28	0.7813	96119.403308
29	0.7817	97283.048858
...	...	...
120	0.7346	0.000000
121	0.8158	75117.971405
122	0.8171	77709.422262
123	0.8173	78039.228020
124	0.8173	78417.664742
125	0.8177	79633.205489
126	0.8182	80230.053053
127	0.8185	81959.234627
128	0.8193	85612.939769
129	0.8197	88585.123545
130	0.8197	89377.333236
131	0.8201	91768.727118
132	0.8227	95646.318878
133	0.8229	96119.403308
134	0.8230	97283.048858
135	0.6867	0.000000
136	0.7575	75117.971405
137	0.7619	77709.422262
138	0.7621	78039.228020
139	0.7621	78417.664742
140	0.7621	79633.205489
141	0.7623	80230.053053
142	0.7521	81959.234627
143	0.7530	85612.939769
144	0.7533	88585.123545
145	0.7540	89377.333236
146	0.7543	91768.727118
147	0.7586	95646.318878
148	0.7587	96119.403308
149	0.7590	97283.048858

150 rows × 2 columns

Groupby $\lambda$

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
final_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
final_acc_grouped_by_lmbda['S.D'] = acc_grouped_by_lmbda.std()
final_acc_grouped_by_lmbda['MIN'] = acc_grouped_by_lmbda.min()
final_acc_grouped_by_lmbda['MAX'] = acc_grouped_by_lmbda.max()
final_acc_grouped_by_lmbda['MED'] = acc_grouped_by_lmbda.median()
final_acc_grouped_by_lmbda.reset_index(inplace=True)
display(final_acc_grouped_by_lmbda)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
2	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
3	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
4	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
5	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
6	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
7	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
8	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
9	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
10	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
11	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
12	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
13	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
14	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_acc_grouped_by_lmbda.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Some histograms

W_2

plt.hist(w_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_W_2

plt.hist(new_big_omeg_w2.flatten(),bins=100,log=True)
#plt.yscale('log')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_2

plt.hist(b_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_b_2

plt.hist(new_big_omeg_b2.flatten(),100,log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

W_3

plt.hist(w_3.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_2

plt.hist(b_3.eval().flatten(), 10)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (10.0, 20.0) non-spk classification

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_14lmbdas_ar1_3lyrs_he1_10_20_non_spk_classify', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 14
a = np.random.uniform(low=10.0, high=20.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 10
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[15.43404942 12.78369385 14.24517591 18.44776132 10.04718856 11.21569121
 16.70749085 18.25852755 11.3670659  15.75093329 18.91321954 12.09202122
 11.8532822  11.0837689 ]
()
[100471.8856191  110837.68904643 112156.91207831 113670.6589685
 118532.82195501 120920.21221172 127836.93850938 142451.75907491
 154340.4941791  157509.33294272 167074.90847268 182585.2755105
 184477.61323199 189132.19543123]
()
([0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264, 0, 100471.88561909726, 110837.68904642553, 112156.91207831142, 113670.65896849529, 118532.8219550075, 120920.21221171896, 127836.93850937962, 142451.7590749133, 154340.49417909654, 157509.33294272498, 167074.90847267784, 182585.27551050478, 184477.6132319904, 189132.1954312264], 150)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(150, 150)

np.array_equal(np_weights[0], np_weights[14])

True

np.array_equal(np_weights[0], np_weights[15])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:135.196543932
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.360579758883 and training accuracy:0.934915006161
validation cost:0.366988688707 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.176190719008 and training accuracy:0.958094716072
validation cost:0.182327464223 and validation accuracy:0.954044103622
Training on :(2, 3)
training cost:0.120868973434 and training accuracy:0.969093739986
validation cost:0.127899214625 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.0940565243363 and training accuracy:0.975456774235
validation cost:0.10124284029 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0779117867351 and training accuracy:0.978456497192
validation cost:0.0847291350365 and validation accuracy:0.974264681339
Training on :(2, 3)
training cost:0.0669855996966 and training accuracy:0.981819808483
validation cost:0.0732256993651 and validation accuracy:0.977941155434
Training on :(2, 3)
training cost:0.0590222999454 and training accuracy:0.983456075191
validation cost:0.0646186545491 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0529175139964 and training accuracy:0.985183179379
validation cost:0.0578845217824 and validation accuracy:0.982536792755
Training on :(2, 3)
training cost:0.04806323722 and training accuracy:0.986364901066
validation cost:0.0524483658373 and validation accuracy:0.983455896378
Training on :(2, 3)
Time taken:136.096754074
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.311708927
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.320827961
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:120920.212212, 6
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:122.943548918
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.810199975967
Training with lmbda:127836.938509, 7
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 15
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.508878946
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.767375946
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.783200025558
Training with lmbda:127836.938509, 22
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.577327013
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.109337091
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:110837.689046, 32
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:124.701102018
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.680162907
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:110837.689046, 47
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.790600001812
Training with lmbda:127836.938509, 52
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0188638195395 and training accuracy:0.998827457428
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Training on :(6, 7)
Time taken:125.390036106
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.392494917
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
Time taken:116.238279104
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:124.730401993
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Repeat:0
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.79439997673
Training with lmbda:182585.275511, 57
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0202516838908 and training accuracy:0.998827457428
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Training on :(6, 7)
Time taken:126.846951008
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:126.507897854
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:125.980268955
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.017852474004 and training accuracy:0.999188244343
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Training on :(6, 7)
Time taken:126.311429977
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.792599976063
Training with lmbda:127836.938509, 82
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:125.003139019
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:125.52621007
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.797699987888
Training with lmbda:182585.275511, 87
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Length of train labels:11087
Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0196488834918 and training accuracy:0.999188244343
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Training on :(6, 7)
Time taken:125.878623009
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:125.201680183
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.995715141
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:112156.912078, 108
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.769100010395
Training with lmbda:113670.658968, 109
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:126.195580959
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.769400000572
Training with lmbda:118532.821955, 110
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.781899988651
Training with lmbda:154340.494179, 114
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.783500015736
Training with lmbda:157509.332943, 115
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0506649985909 and training accuracy:0.986910283566
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Training on :(2, 3)
Time taken:123.36582303
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.827000021935
Training with lmbda:154340.494179, 129
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:123.21735096
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.827600002289
Training with lmbda:157509.332943, 130
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:0, 135
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Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.771499991417
Training with lmbda:184477.613232, 148
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
training cost:0.0508863590658 and training accuracy:0.987546563148
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Training on :(2, 3)
Time taken:125.09168601
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Repeat:0
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
training cost:0.0295238066465 and training accuracy:0.996878027916
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Training on :(4, 5)
Time taken:116.6801579
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Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:129.585517883
Method 3 test accuracy:0.771700024605
Training with lmbda:189132.195431, 149
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
training cost:0.0202924311161 and training accuracy:0.998827457428
validation cost:0.0187365394086 and validation accuracy:1.0
Training on :(6, 7)
Time taken:127.060585976
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
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Training on :(8, 9)
training cost:0.229917123914 and training accuracy:0.957254588604
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Training on :(8, 9)
training cost:0.142005473375 and training accuracy:0.965729176998
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
training cost:0.0738874822855 and training accuracy:0.979977667332
validation cost:0.0762765184045 and validation accuracy:0.982109248638
Training on :(8, 9)
training cost:0.067549020052 and training accuracy:0.981840193272
validation cost:0.0696138516068 and validation accuracy:0.984934091568
Training on :(8, 9)
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validation cost:0.0642497912049 and validation accuracy:0.984934091568
Training on :(8, 9)
training cost:0.0583306066692 and training accuracy:0.984261512756
validation cost:0.0598219111562 and validation accuracy:0.987758934498
Training on :(8, 9)
Time taken:128.393730164
Method 3 test accuracy:0.771799981594
Total time:93722.8331778

Final accuracies

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_10_20_non_spk_classify.csv')
final_test_acc

	Method3	lambdas
0	0.7295	0.000000
1	0.8072	100471.885619
2	0.8090	110837.689046
3	0.8091	112156.912078
4	0.8091	113670.658968
5	0.8097	118532.821955
6	0.8102	120920.212212
7	0.8114	127836.938509
8	0.8123	142451.759075
9	0.8140	154340.494179
10	0.8144	157509.332943
11	0.8140	167074.908473
12	0.8157	182585.275511
13	0.8159	184477.613232
14	0.8163	189132.195431
15	0.7188	0.000000
16	0.7819	100471.885619
17	0.7826	110837.689046
18	0.7827	112156.912078
19	0.7827	113670.658968
20	0.7828	118532.821955
21	0.7832	120920.212212
22	0.7842	127836.938509
23	0.7861	142451.759075
24	0.7873	154340.494179
25	0.7886	157509.332943
26	0.7898	167074.908473
27	0.7904	182585.275511
28	0.7905	184477.613232
29	0.7909	189132.195431
...	...	...
120	0.7346	0.000000
121	0.8228	100471.885619
122	0.8240	110837.689046
123	0.8243	112156.912078
124	0.8243	113670.658968
125	0.8248	118532.821955
126	0.8249	120920.212212
127	0.8257	127836.938509
128	0.8270	142451.759075
129	0.8276	154340.494179
130	0.8276	157509.332943
131	0.8280	167074.908473
132	0.8288	182585.275511
133	0.8291	184477.613232
134	0.8296	189132.195431
135	0.6867	0.000000
136	0.7600	100471.885619
137	0.7626	110837.689046
138	0.7631	112156.912078
139	0.7635	113670.658968
140	0.7638	118532.821955
141	0.7643	120920.212212
142	0.7647	127836.938509
143	0.7671	142451.759075
144	0.7692	154340.494179
145	0.7695	157509.332943
146	0.7704	167074.908473
147	0.7715	182585.275511
148	0.7717	184477.613232
149	0.7718	189132.195431

150 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
final_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
final_acc_grouped_by_lmbda['S.D'] = acc_grouped_by_lmbda.std()
final_acc_grouped_by_lmbda['MIN'] = acc_grouped_by_lmbda.min()
final_acc_grouped_by_lmbda['MAX'] = acc_grouped_by_lmbda.max()
final_acc_grouped_by_lmbda['MED'] = acc_grouped_by_lmbda.median()
final_acc_grouped_by_lmbda.reset_index(inplace=True)
display(final_acc_grouped_by_lmbda)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	100471.885619	0.78694	0.020593	0.7600	0.8228	0.78455
2	110837.689046	0.78835	0.020678	0.7626	0.8240	0.78550
3	112156.912078	0.78858	0.020706	0.7631	0.8243	0.78575
4	113670.658968	0.78866	0.020647	0.7635	0.8243	0.78585
5	118532.821955	0.78888	0.021238	0.7638	0.8248	0.78630
6	120920.212212	0.78930	0.021262	0.7643	0.8249	0.78690
7	127836.938509	0.79036	0.021217	0.7647	0.8257	0.78750
8	142451.759075	0.79277	0.020593	0.7671	0.8270	0.78950
9	154340.494179	0.79669	0.018245	0.7692	0.8276	0.79450
10	157509.332943	0.79754	0.018844	0.7695	0.8276	0.79505
11	167074.908473	0.79855	0.018636	0.7704	0.8280	0.79605
12	182585.275511	0.79986	0.018529	0.7715	0.8288	0.79720
13	184477.613232	0.80001	0.018600	0.7717	0.8291	0.79740
14	189132.195431	0.80045	0.018781	0.7718	0.8296	0.79775

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_acc_grouped_by_lmbda.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Combine with previous $\lambda$s

prev_final_test_acc = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_75_10_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda = prev_final_test_acc.groupby('lambdas')
prev_final_acc_grouped_by_lmbda = prev_acc_grouped_by_lmbda.mean()
prev_final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda['S.D'] = prev_acc_grouped_by_lmbda.std()
prev_final_acc_grouped_by_lmbda['MIN'] = prev_acc_grouped_by_lmbda.min()
prev_final_acc_grouped_by_lmbda['MAX'] = prev_acc_grouped_by_lmbda.max()
prev_final_acc_grouped_by_lmbda['MED'] = prev_acc_grouped_by_lmbda.median()
prev_final_acc_grouped_by_lmbda.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
2	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
3	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
4	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
5	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
6	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
7	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
8	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
9	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
10	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
11	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
12	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
13	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
14	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440

df2 = final_acc_grouped_by_lmbda.copy(deep=True)
df2.drop([0], inplace=True)

df1 = prev_final_acc_grouped_by_lmbda.copy(deep=True)
df1.drop([0], inplace=True)

final_df = pd.concat([df1, df2], axis=0)
display(final_df)

Combined plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_df.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.xlabel('$\lambda$')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Some histograms

W_2

plt.hist(w_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_W_2

plt.hist(new_big_omeg_w2.flatten(),bins=100,log=True)
#plt.yscale('log')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_2

plt.hist(b_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_b_2

plt.hist(new_big_omeg_b2.flatten(),100,log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

W_3

plt.hist(w_3.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_3

plt.hist(b_3.eval().flatten(), 10)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (20.0, 45.0) non-spk classification

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_14lmbdas_ar1_3lyrs_he1_20_45_non_spk-classify', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 14
a = np.random.uniform(low=20.0, high=45.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 10
a = a.tolist()*n_reps
print(a, len(a))

[33.58512354 26.95923463 30.61293977 41.11940331 20.1179714  23.03922802
 36.76872712 40.64631888 23.41766474 34.37733324 42.28304886 25.23005305
 24.63320549 22.70942226]
()
[201179.71404774 227094.22261606 230392.28019578 234176.64742124
 246332.05488752 252300.5305293  269592.34627345 306129.39768728
 335851.23544774 343773.33235681 367687.27118169 406463.18877626
 411194.03307998 422830.48857807]
()
([201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606, 201179.71404774312, 227094.22261606378, 230392.28019577856, 234176.64742123825, 246332.05488751875, 252300.5305292974, 269592.3462734491, 306129.3976872833, 335851.23544774135, 343773.3323568125, 367687.27118169464, 406463.1887762619, 411194.03307997587, 422830.48857806606], 140)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(140, 140)

np.array_equal(np_weights[0], np_weights[13])

True

np.array_equal(np_weights[0], np_weights[14])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:201179.714048, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:127.148087978
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.365370094776 and training accuracy:0.935187697411
validation cost:0.371715277433 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.180861055851 and training accuracy:0.958367407322
validation cost:0.186769783497 and validation accuracy:0.954963207245
Training on :(2, 3)
training cost:0.125274881721 and training accuracy:0.96945732832
validation cost:0.131964370608 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.0983472391963 and training accuracy:0.975274980068
validation cost:0.105192996562 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0821335017681 and training accuracy:0.978456497192
validation cost:0.0886770859361 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.0711426585913 and training accuracy:0.981092631817
validation cost:0.0771973207593 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0631121173501 and training accuracy:0.983365178108
validation cost:0.0686135366559 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0569368302822 and training accuracy:0.985001385212
validation cost:0.0618881620467 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0520118623972 and training accuracy:0.986183047295
validation cost:0.0564433187246 and validation accuracy:0.982536792755
Training on :(2, 3)
Time taken:120.764403105
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.24794845283 and training accuracy:0.980000019073
validation cost:0.249291822314 and validation accuracy:0.984205305576
Training on :(4, 5)
training cost:0.118868738413 and training accuracy:0.990341484547
validation cost:0.113860405982 and validation accuracy:0.995064139366
Training on :(4, 5)
training cost:0.0787904113531 and training accuracy:0.99385368824
validation cost:0.0720571130514 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0599230527878 and training accuracy:0.994536578655
validation cost:0.0527997128665 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0489865280688 and training accuracy:0.995024383068
validation cost:0.041881814599 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0418191589415 and training accuracy:0.996195137501
validation cost:0.034874048084 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0367281958461 and training accuracy:0.996195137501
validation cost:0.0299916658551 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0329071059823 and training accuracy:0.996487796307
validation cost:0.0263924896717 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0299187675118 and training accuracy:0.996780514717
validation cost:0.0236237086356 and validation accuracy:1.0
Training on :(4, 5)
Time taken:113.720855951
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.173049256206 and training accuracy:0.991521596909
validation cost:0.166700169444 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0771193131804 and training accuracy:0.995670616627
validation cost:0.074042275548 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0513040199876 and training accuracy:0.997203946114
validation cost:0.0491839013994 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0394318439066 and training accuracy:0.997745096684
validation cost:0.0377111323178 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0325443930924 and training accuracy:0.998196065426
validation cost:0.0310354270041 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0280036143959 and training accuracy:0.998376488686
validation cost:0.0266265943646 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0247591622174 and training accuracy:0.998556852341
validation cost:0.0234768856317 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0223094057292 and training accuracy:0.9987372756
validation cost:0.0211003124714 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0203834157437 and training accuracy:0.999007821083
validation cost:0.0192345716059 and validation accuracy:1.0
Training on :(6, 7)
Time taken:121.840325832
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.238327682018 and training accuracy:0.957254588604
validation cost:0.239375770092 and validation accuracy:0.951977372169
Training on :(8, 9)
training cost:0.145161107183 and training accuracy:0.965822339058
validation cost:0.146721929312 and validation accuracy:0.960451960564
Training on :(8, 9)
training cost:0.112319603562 and training accuracy:0.972061812878
validation cost:0.114133246243 and validation accuracy:0.972693026066
Training on :(8, 9)
training cost:0.0944448187947 and training accuracy:0.975414395332
validation cost:0.0961641073227 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0827401503921 and training accuracy:0.978208243847
validation cost:0.084208227694 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.074293859303 and training accuracy:0.980350136757
validation cost:0.07546094805 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0678328201175 and training accuracy:0.981653928757
validation cost:0.0686981901526 and validation accuracy:0.984934091568
Training on :(8, 9)
training cost:0.0626917257905 and training accuracy:0.983330249786
validation cost:0.0632754191756 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0584801472723 and training accuracy:0.984447777271
validation cost:0.058807272464 and validation accuracy:0.987758934498
Training on :(8, 9)
Time taken:117.867750168
Method 3 test accuracy:0.818599998951
Training with lmbda:227094.222616, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:125.802834034
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.365877747536 and training accuracy:0.935187697411
validation cost:0.372216492891 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.181316152215 and training accuracy:0.958367407322
validation cost:0.187206238508 and validation accuracy:0.954963207245
Training on :(2, 3)
training cost:0.125678807497 and training accuracy:0.96945732832
validation cost:0.132344454527 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.098721139133 and training accuracy:0.975184082985
validation cost:0.105546437204 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0824863761663 and training accuracy:0.978456497192
validation cost:0.0890158265829 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.0714795216918 and training accuracy:0.981092631817
validation cost:0.0775276124477 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0634348317981 and training accuracy:0.983365178108
validation cost:0.0689372122288 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0572472549975 and training accuracy:0.985001385212
validation cost:0.0622052662075 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.052311129868 and training accuracy:0.986183047295
validation cost:0.0567540377378 and validation accuracy:0.982536792755
Training on :(2, 3)
Time taken:120.589581013
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.2501706779 and training accuracy:0.97990244627
validation cost:0.251581251621 and validation accuracy:0.983218193054
Training on :(4, 5)
training cost:0.120415613055 and training accuracy:0.990438997746
validation cost:0.115474686027 and validation accuracy:0.995064139366
Training on :(4, 5)
training cost:0.0799827948213 and training accuracy:0.993951201439
validation cost:0.0733000263572 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0609000697732 and training accuracy:0.994536578655
validation cost:0.0538155138493 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0498200505972 and training accuracy:0.994926810265
validation cost:0.0427470505238 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0425490289927 and training accuracy:0.996097564697
validation cost:0.0356303788722 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0373813584447 and training accuracy:0.996195137501
validation cost:0.0306670609862 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.033500123769 and training accuracy:0.996487796307
validation cost:0.0270046833903 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0304628070444 and training accuracy:0.996780514717
validation cost:0.0241846702993 and validation accuracy:1.0
Training on :(4, 5)
Time taken:112.552898884
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.17500410974 and training accuracy:0.991521596909
validation cost:0.168654978275 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0783808976412 and training accuracy:0.995670616627
validation cost:0.0752899199724 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0523045621812 and training accuracy:0.997203946114
validation cost:0.0501713864505 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0402813367546 and training accuracy:0.997654914856
validation cost:0.0385502129793 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0332912020385 and training accuracy:0.998196065426
validation cost:0.0317739285529 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0286734439433 and training accuracy:0.998376488686
validation cost:0.0272907335311 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0253692511469 and training accuracy:0.998647093773
validation cost:0.024082634598 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0228712595999 and training accuracy:0.9987372756
validation cost:0.0216586645693 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0209049768746 and training accuracy:0.998917639256
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.825900018215
Training with lmbda:234176.647421, 3
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:335851.235448, 8
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:343773.332357, 9
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.434417009
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:406463.188776, 11
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:422830.488578, 13
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:201179.714048, 14
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.797299981117
Training with lmbda:343773.332357, 23
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.797699987888
Training with lmbda:367687.271182, 24
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.822700023651
Training with lmbda:367687.271182, 38
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.823199987411
Training with lmbda:406463.188776, 39
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:411194.03308, 40
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:121.025403023
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.809800028801
Training with lmbda:227094.222616, 43
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:117.840037823
Method 3 test accuracy:0.812900006771
Training with lmbda:230392.280196, 44
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:246332.054888, 46
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:306129.397687, 49
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:335851.235448, 50
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:343773.332357, 51
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.811500012875
Training with lmbda:406463.188776, 53
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.812200009823
Training with lmbda:411194.03308, 54
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:234176.647421, 59
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:335851.235448, 64
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:335851.235448, 78
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.802500009537
Training with lmbda:343773.332357, 79
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:422830.488578, 83
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.805000007153
Training with lmbda:201179.714048, 84
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.83520001173
Training with lmbda:343773.332357, 93
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:120.188527822
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Training with lmbda:367687.271182, 94
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:201179.714048, 98
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Train features:(10738, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.791700005531
Training with lmbda:252300.530529, 103
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
Time taken:122.789484024
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:227094.222616, 113
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:269592.346273, 118
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:406463.188776, 123
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.579171896
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.834699988365
Training with lmbda:422830.488578, 125
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:201179.714048, 126
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
training cost:0.245449200273 and training accuracy:0.956788957119
validation cost:0.247818484902 and validation accuracy:0.94915252924
Training on :(8, 9)
training cost:0.15225559473 and training accuracy:0.965449810028
validation cost:0.155336856842 and validation accuracy:0.963276863098
Training on :(8, 9)
training cost:0.119462020695 and training accuracy:0.971130549908
validation cost:0.122695922852 and validation accuracy:0.970809817314
Training on :(8, 9)
training cost:0.101629391313 and training accuracy:0.974296867847
validation cost:0.104745365679 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.0899430587888 and training accuracy:0.976252555847
validation cost:0.092834636569 and validation accuracy:0.977401137352
Training on :(8, 9)
training cost:0.0814886391163 and training accuracy:0.978766977787
validation cost:0.0841259434819 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0749905630946 and training accuracy:0.980629563332
validation cost:0.0773726925254 and validation accuracy:0.982109248638
Training on :(8, 9)
training cost:0.0697880089283 and training accuracy:0.981747090816
validation cost:0.0719266831875 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.065499715507 and training accuracy:0.982585191727
validation cost:0.0674137473106 and validation accuracy:0.985875725746
Training on :(8, 9)
Time taken:117.23761487
Method 3 test accuracy:0.778299987316
Training with lmbda:422830.488578, 139
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.203907415271 and training accuracy:0.997570693493
validation cost:0.201984629035 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0566555894911 and training accuracy:0.99809128046
validation cost:0.0579187460244 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0322347804904 and training accuracy:0.998351573944
validation cost:0.0339787490666 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0228093471378 and training accuracy:0.998525083065
validation cost:0.0246704109013 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0178289748728 and training accuracy:0.998525083065
validation cost:0.0197088513523 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0147348884493 and training accuracy:0.998698592186
validation cost:0.0165966041386 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126142920926 and training accuracy:0.998698592186
validation cost:0.0144430585206 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.011062421836 and training accuracy:0.998872101307
validation cost:0.0128502687439 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00987247936428 and training accuracy:0.99895888567
validation cost:0.0116164442152 and validation accuracy:0.997366130352
Training on :(0, 1)
Time taken:125.867727995
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.370331466198 and training accuracy:0.940823554993
validation cost:0.374528437853 and validation accuracy:0.945772051811
Training on :(2, 3)
training cost:0.181225240231 and training accuracy:0.961185336113
validation cost:0.184606671333 and validation accuracy:0.957720577717
Training on :(2, 3)
training cost:0.125446796417 and training accuracy:0.971638917923
validation cost:0.129105940461 and validation accuracy:0.96875
Training on :(2, 3)
training cost:0.0987759530544 and training accuracy:0.975184082985
validation cost:0.10244654119 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0827929973602 and training accuracy:0.97936552763
validation cost:0.0862410739064 and validation accuracy:0.977941155434
Training on :(2, 3)
training cost:0.0719656124711 and training accuracy:0.982456147671
validation cost:0.0750799998641 and validation accuracy:0.980698525906
Training on :(2, 3)
training cost:0.064051784575 and training accuracy:0.984819591045
validation cost:0.0668069422245 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0579576864839 and training accuracy:0.986092150211
validation cost:0.0603550747037 and validation accuracy:0.983455896378
Training on :(2, 3)
training cost:0.0530875921249 and training accuracy:0.987182974815
validation cost:0.0551411099732 and validation accuracy:0.985294103622
Training on :(2, 3)
Time taken:120.720551014
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.26400834322 and training accuracy:0.979609727859
validation cost:0.267522484064 and validation accuracy:0.984205305576
Training on :(4, 5)
training cost:0.1295915097 and training accuracy:0.989268302917
validation cost:0.126460760832 and validation accuracy:0.994077026844
Training on :(4, 5)
training cost:0.0870080962777 and training accuracy:0.993463397026
validation cost:0.0817840844393 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0665907040238 and training accuracy:0.994439005852
validation cost:0.0607018247247 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0546052828431 and training accuracy:0.994926810265
validation cost:0.0485374778509 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0466879718006 and training accuracy:0.995512187481
validation cost:0.0406330488622 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0410391390324 and training accuracy:0.996097564697
validation cost:0.0350810401142 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0367872752249 and training accuracy:0.996487796307
validation cost:0.03096168302 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0334576927125 and training accuracy:0.996975600719
validation cost:0.0277787614614 and validation accuracy:1.0
Training on :(4, 5)
Time taken:112.476815939
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.182829216123 and training accuracy:0.992423534393
validation cost:0.175385028124 and validation accuracy:0.992700755596
Training on :(6, 7)
training cost:0.0861289873719 and training accuracy:0.996031403542
validation cost:0.0822580829263 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.058736551553 and training accuracy:0.997294127941
validation cost:0.0559637956321 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0457656420767 and training accuracy:0.997745096684
validation cost:0.0434623248875 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0380929000676 and training accuracy:0.998105883598
validation cost:0.0360432006419 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.032964065671 and training accuracy:0.998556852341
validation cost:0.0310731567442 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0292615126818 and training accuracy:0.998647093773
validation cost:0.0274822432548 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0264442488551 and training accuracy:0.998917639256
validation cost:0.0247489884496 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.024216607213 and training accuracy:0.998917639256
validation cost:0.0225889328867 and validation accuracy:1.0
Training on :(6, 7)
Time taken:121.350713968
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.246175333858 and training accuracy:0.956788957119
validation cost:0.248546674848 and validation accuracy:0.94915252924
Training on :(8, 9)
training cost:0.152743116021 and training accuracy:0.965449810028
validation cost:0.155828818679 and validation accuracy:0.963276863098
Training on :(8, 9)
training cost:0.119868867099 and training accuracy:0.971130549908
validation cost:0.123107522726 and validation accuracy:0.970809817314
Training on :(8, 9)
training cost:0.101998910308 and training accuracy:0.974296867847
validation cost:0.105122111738 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.0902915075421 and training accuracy:0.976252555847
validation cost:0.0931931585073 and validation accuracy:0.977401137352
Training on :(8, 9)
training cost:0.0818230360746 and training accuracy:0.978487610817
validation cost:0.0844729542732 and validation accuracy:0.979284346104
Training on :(8, 9)
training cost:0.0753156021237 and training accuracy:0.980536401272
validation cost:0.0777129530907 and validation accuracy:0.982109248638
Training on :(8, 9)
training cost:0.0701029971242 and training accuracy:0.981747090816
validation cost:0.0722588077188 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0658065751195 and training accuracy:0.982585191727
validation cost:0.0677396208048 and validation accuracy:0.985875725746
Training on :(8, 9)
Time taken:117.946047068
Method 3 test accuracy:0.777899980545
Total time:84589.9557409

Final accuracy

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_20_45-non_spk.csv')
final_test_acc

	Method3	lambdas
0	0.8186	201179.714048
1	0.8258	227094.222616
2	0.8259	230392.280196
3	0.8261	234176.647421
4	0.8263	246332.054888
5	0.8266	252300.530529
6	0.8276	269592.346273
7	0.8221	306129.397687
8	0.8232	335851.235448
9	0.8232	343773.332357
10	0.8244	367687.271182
11	0.8178	406463.188776
12	0.8179	411194.033080
13	0.8178	422830.488578
14	0.7921	201179.714048
15	0.7949	227094.222616
16	0.7952	230392.280196
17	0.7952	234176.647421
18	0.7941	246332.054888
19	0.7940	252300.530529
20	0.7955	269592.346273
21	0.7966	306129.397687
22	0.7973	335851.235448
23	0.7977	343773.332357
24	0.7986	367687.271182
25	0.7995	406463.188776
26	0.7993	411194.033080
27	0.7996	422830.488578
28	0.8020	201179.714048
29	0.8033	227094.222616
...	...	...
110	0.7999	411194.033080
111	0.7999	422830.488578
112	0.8303	201179.714048
113	0.8311	227094.222616
114	0.8311	230392.280196
115	0.8311	234176.647421
116	0.8315	246332.054888
117	0.8313	252300.530529
118	0.8314	269592.346273
119	0.8330	306129.397687
120	0.8334	335851.235448
121	0.8335	343773.332357
122	0.8340	367687.271182
123	0.8346	406463.188776
124	0.8347	411194.033080
125	0.8346	422830.488578
126	0.7731	201179.714048
127	0.7757	227094.222616
128	0.7758	230392.280196
129	0.7759	234176.647421
130	0.7767	246332.054888
131	0.7769	252300.530529
132	0.7769	269592.346273
133	0.7781	306129.397687
134	0.7778	335851.235448
135	0.7781	343773.332357
136	0.7779	367687.271182
137	0.7779	406463.188776
138	0.7783	411194.033080
139	0.7779	422830.488578

140 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
final_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
final_acc_grouped_by_lmbda['S.D'] = acc_grouped_by_lmbda.std()
final_acc_grouped_by_lmbda['MIN'] = acc_grouped_by_lmbda.min()
final_acc_grouped_by_lmbda['MAX'] = acc_grouped_by_lmbda.max()
final_acc_grouped_by_lmbda['MED'] = acc_grouped_by_lmbda.median()
final_acc_grouped_by_lmbda.reset_index(inplace=True)
display(final_acc_grouped_by_lmbda)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	201179.714048	0.80312	0.018350	0.7731	0.8303	0.79940
1	227094.222616	0.80550	0.018698	0.7757	0.8311	0.80060
2	230392.280196	0.80567	0.018672	0.7758	0.8311	0.80065
3	234176.647421	0.80583	0.018595	0.7759	0.8311	0.80085
4	246332.054888	0.80623	0.018735	0.7767	0.8315	0.80135
5	252300.530529	0.80687	0.019128	0.7769	0.8345	0.80195
6	269592.346273	0.80868	0.018645	0.7769	0.8352	0.80590
7	306129.397687	0.81075	0.019335	0.7781	0.8365	0.81640
8	335851.235448	0.81119	0.019834	0.7778	0.8352	0.81790
9	343773.332357	0.81128	0.019692	0.7781	0.8350	0.81765
10	367687.271182	0.81151	0.019817	0.7779	0.8360	0.81590
11	406463.188776	0.81217	0.019033	0.7779	0.8378	0.80835
12	411194.033080	0.81229	0.018940	0.7783	0.8378	0.80845
13	422830.488578	0.81246	0.019064	0.7779	0.8383	0.80875

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_acc_grouped_by_lmbda.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Combine with the previous $\lambda$s

prev_final_test_acc1 = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_75_10_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda1 = prev_final_test_acc1.groupby('lambdas')
prev_final_acc_grouped_by_lmbda1 = prev_acc_grouped_by_lmbda1.mean()
prev_final_acc_grouped_by_lmbda1.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda1['S.D'] = prev_acc_grouped_by_lmbda1.std()
prev_final_acc_grouped_by_lmbda1['MIN'] = prev_acc_grouped_by_lmbda1.min()
prev_final_acc_grouped_by_lmbda1['MAX'] = prev_acc_grouped_by_lmbda1.max()
prev_final_acc_grouped_by_lmbda1['MED'] = prev_acc_grouped_by_lmbda1.median()
prev_final_acc_grouped_by_lmbda1.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda1)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
2	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
3	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
4	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
5	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
6	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
7	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
8	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
9	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
10	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
11	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
12	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
13	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
14	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440

prev_final_test_acc2 = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_10_20_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda2 = prev_final_test_acc2.groupby('lambdas')
prev_final_acc_grouped_by_lmbda2 = prev_acc_grouped_by_lmbda2.mean()
prev_final_acc_grouped_by_lmbda2.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda2['S.D'] = prev_acc_grouped_by_lmbda2.std()
prev_final_acc_grouped_by_lmbda2['MIN'] = prev_acc_grouped_by_lmbda2.min()
prev_final_acc_grouped_by_lmbda2['MAX'] = prev_acc_grouped_by_lmbda2.max()
prev_final_acc_grouped_by_lmbda2['MED'] = prev_acc_grouped_by_lmbda2.median()
prev_final_acc_grouped_by_lmbda2.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda2)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	100471.885619	0.78694	0.020593	0.7600	0.8228	0.78455
2	110837.689046	0.78835	0.020678	0.7626	0.8240	0.78550
3	112156.912078	0.78858	0.020706	0.7631	0.8243	0.78575
4	113670.658968	0.78866	0.020647	0.7635	0.8243	0.78585
5	118532.821955	0.78888	0.021238	0.7638	0.8248	0.78630
6	120920.212212	0.78930	0.021262	0.7643	0.8249	0.78690
7	127836.938509	0.79036	0.021217	0.7647	0.8257	0.78750
8	142451.759075	0.79277	0.020593	0.7671	0.8270	0.78950
9	154340.494179	0.79669	0.018245	0.7692	0.8276	0.79450
10	157509.332943	0.79754	0.018844	0.7695	0.8276	0.79505
11	167074.908473	0.79855	0.018636	0.7704	0.8280	0.79605
12	182585.275511	0.79986	0.018529	0.7715	0.8288	0.79720
13	184477.613232	0.80001	0.018600	0.7717	0.8291	0.79740
14	189132.195431	0.80045	0.018781	0.7718	0.8296	0.79775

df3 = final_acc_grouped_by_lmbda.copy(deep=True)
df3.drop([0], inplace=True)

df2 = prev_final_acc_grouped_by_lmbda2.copy(deep=True)
df2.drop([0], inplace=True)

df1 = prev_final_acc_grouped_by_lmbda1.copy(deep=True)
df1.drop([0], inplace=True)

final_df = pd.concat([df1, df2, df3], axis=0)
display(final_df)

	lambdas	MEAN	S.D	MIN	MAX	MED
1	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
2	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
3	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
4	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
5	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
6	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
7	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
8	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
9	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
10	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
11	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
12	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
13	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
14	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440
1	100471.885619	0.78694	0.020593	0.7600	0.8228	0.78455
2	110837.689046	0.78835	0.020678	0.7626	0.8240	0.78550
3	112156.912078	0.78858	0.020706	0.7631	0.8243	0.78575
4	113670.658968	0.78866	0.020647	0.7635	0.8243	0.78585
5	118532.821955	0.78888	0.021238	0.7638	0.8248	0.78630
6	120920.212212	0.78930	0.021262	0.7643	0.8249	0.78690
7	127836.938509	0.79036	0.021217	0.7647	0.8257	0.78750
8	142451.759075	0.79277	0.020593	0.7671	0.8270	0.78950
9	154340.494179	0.79669	0.018245	0.7692	0.8276	0.79450
10	157509.332943	0.79754	0.018844	0.7695	0.8276	0.79505
11	167074.908473	0.79855	0.018636	0.7704	0.8280	0.79605
12	182585.275511	0.79986	0.018529	0.7715	0.8288	0.79720
13	184477.613232	0.80001	0.018600	0.7717	0.8291	0.79740
14	189132.195431	0.80045	0.018781	0.7718	0.8296	0.79775
1	227094.222616	0.80550	0.018698	0.7757	0.8311	0.80060
2	230392.280196	0.80567	0.018672	0.7758	0.8311	0.80065
3	234176.647421	0.80583	0.018595	0.7759	0.8311	0.80085
4	246332.054888	0.80623	0.018735	0.7767	0.8315	0.80135
5	252300.530529	0.80687	0.019128	0.7769	0.8345	0.80195
6	269592.346273	0.80868	0.018645	0.7769	0.8352	0.80590
7	306129.397687	0.81075	0.019335	0.7781	0.8365	0.81640
8	335851.235448	0.81119	0.019834	0.7778	0.8352	0.81790
9	343773.332357	0.81128	0.019692	0.7781	0.8350	0.81765
10	367687.271182	0.81151	0.019817	0.7779	0.8360	0.81590
11	406463.188776	0.81217	0.019033	0.7779	0.8378	0.80835
12	411194.033080	0.81229	0.018940	0.7783	0.8378	0.80845
13	422830.488578	0.81246	0.019064	0.7779	0.8383	0.80875

Combined plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_df.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.xlabel('$\lambda$')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (45.0, 65.0) non-spk classification

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_14lmbdas_ar1_3lyrs_he1_45_65_non_spk_classify', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 14
a = np.random.uniform(low=45.0, high=65.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 10
a = a.tolist()*n_reps
print(a, len(a))

[55.86809884 50.5673877  53.49035181 61.89552265 45.09437712 47.43138242
 58.41498169 61.5170551  47.73413179 56.50186659 62.82643909 49.18404244
 48.70656439 47.16753781]
()
[450943.77123819 471675.37809285 474313.82415662 477341.31793699
 487065.64391002 491840.42442344 505673.87701876 534903.51814983
 558680.98835819 565018.66588545 584149.81694536 615170.55102101
 618955.22646398 628264.39086245]
()
([450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528, 450943.7712381945, 471675.378092851, 474313.82415662287, 477341.3179369906, 487065.643910015, 491840.424423438, 505673.8770187592, 534903.5181498266, 558680.9883581931, 565018.66588545, 584149.8169453557, 615170.5510210096, 618955.2264639807, 628264.3908624528], 140)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(140, 140)

np.array_equal(np_weights[0], np_weights[13])

True

np.array_equal(np_weights[0], np_weights[14])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:450943.771238, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:130.454847097
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.369670182467 and training accuracy:0.935914933681
validation cost:0.375963538885 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.184623375535 and training accuracy:0.958458304405
validation cost:0.190390229225 and validation accuracy:0.956801474094
Training on :(2, 3)
training cost:0.128535434604 and training accuracy:0.96918463707
validation cost:0.135043501854 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.101328678429 and training accuracy:0.974729597569
validation cost:0.108018510044 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0849213078618 and training accuracy:0.978456497192
validation cost:0.0913636088371 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.07377756387 and training accuracy:0.980547249317
validation cost:0.0797813758254 and validation accuracy:0.976102948189
Training on :(2, 3)
training cost:0.0656215324998 and training accuracy:0.983365178108
validation cost:0.0711211711168 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0593418516219 and training accuracy:0.984819591045
validation cost:0.0643283501267 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0543255321681 and training accuracy:0.986001253128
validation cost:0.0588221997023 and validation accuracy:0.982536792755
Training on :(2, 3)
Time taken:121.150041103
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.265115320683 and training accuracy:0.979512214661
validation cost:0.267008721828 and validation accuracy:0.982231020927
Training on :(4, 5)
training cost:0.130719467998 and training accuracy:0.989853680134
validation cost:0.126261383295 and validation accuracy:0.995064139366
Training on :(4, 5)
training cost:0.0877870619297 and training accuracy:0.993756115437
validation cost:0.081469386816 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0672105625272 and training accuracy:0.994146347046
validation cost:0.0604062378407 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0551477111876 and training accuracy:0.994829297066
validation cost:0.0483011826873 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0471838973463 and training accuracy:0.995707333088
validation cost:0.0404557548463 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0415033176541 and training accuracy:0.99590241909
validation cost:0.034953918308 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0372247211635 and training accuracy:0.996390223503
validation cost:0.0308730620891 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.033870857209 and training accuracy:0.996682941914
validation cost:0.0277195628732 and validation accuracy:1.0
Training on :(4, 5)
Time taken:116.514461994
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.189197048545 and training accuracy:0.991611778736
validation cost:0.182851299644 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0874088183045 and training accuracy:0.995580434799
validation cost:0.0842503905296 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0592690669 and training accuracy:0.997023522854
validation cost:0.0570772215724 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0460706725717 and training accuracy:0.997564733028
validation cost:0.0442968718708 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0382941029966 and training accuracy:0.998015701771
validation cost:0.0367477945983 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0331046655774 and training accuracy:0.998376488686
validation cost:0.0317033939064 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0293607730418 and training accuracy:0.998556852341
validation cost:0.0280617624521 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0265118610114 and training accuracy:0.998647093773
validation cost:0.0252914763987 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0242579709738 and training accuracy:0.998917639256
validation cost:0.023100912571 and validation accuracy:1.0
Training on :(6, 7)
Time taken:127.303239822
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.256253153086 and training accuracy:0.957440853119
validation cost:0.257125467062 and validation accuracy:0.951977372169
Training on :(8, 9)
training cost:0.156942814589 and training accuracy:0.966008543968
validation cost:0.158124446869 and validation accuracy:0.95951038599
Training on :(8, 9)
training cost:0.122185394168 and training accuracy:0.970944285393
validation cost:0.12352565676 and validation accuracy:0.96798491478
Training on :(8, 9)
training cost:0.103442959487 and training accuracy:0.974762499332
validation cost:0.104706570506 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0912368521094 and training accuracy:0.976997554302
validation cost:0.0923114642501 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.0824397429824 and training accuracy:0.979418873787
validation cost:0.0832918807864 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0756992101669 and training accuracy:0.980536401272
validation cost:0.0763282626867 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0703127384186 and training accuracy:0.981933295727
validation cost:0.0707345381379 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0658803209662 and training accuracy:0.983423352242
validation cost:0.0661128386855 and validation accuracy:0.985875725746
Training on :(8, 9)
Time taken:118.467080116
Method 3 test accuracy:0.813399970531
Training with lmbda:471675.378093, 1
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:126.208035946
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.369981199503 and training accuracy:0.935914933681
validation cost:0.376271218061 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.184888854623 and training accuracy:0.958458304405
validation cost:0.190646827221 and validation accuracy:0.956801474094
Training on :(2, 3)
training cost:0.128759935498 and training accuracy:0.96918463707
validation cost:0.135256066918 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.101530574262 and training accuracy:0.974729597569
validation cost:0.108209870756 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.085108101368 and training accuracy:0.978456497192
validation cost:0.0915433987975 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.0739539563656 and training accuracy:0.980456292629
validation cost:0.0799549221992 and validation accuracy:0.975183844566
Training on :(2, 3)
training cost:0.0657889097929 and training accuracy:0.98327422142
validation cost:0.0712874531746 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0595018938184 and training accuracy:0.984819591045
validation cost:0.0644905045629 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0544786304235 and training accuracy:0.986001253128
validation cost:0.0589795336127 and validation accuracy:0.982536792755
Training on :(2, 3)
Time taken:120.772943974
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.266242653131 and training accuracy:0.979414641857
validation cost:0.268175244331 and validation accuracy:0.981243848801
Training on :(4, 5)
training cost:0.131490364671 and training accuracy:0.989853680134
validation cost:0.127072110772 and validation accuracy:0.995064139366
Training on :(4, 5)
training cost:0.0883641988039 and training accuracy:0.993756115437
validation cost:0.0820760428905 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0676730647683 and training accuracy:0.994146347046
validation cost:0.0608913600445 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0555352158844 and training accuracy:0.994829297066
validation cost:0.04870704934 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0475194342434 and training accuracy:0.995707333088
validation cost:0.0408069565892 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0418006815016 and training accuracy:0.995804905891
validation cost:0.0352650918067 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.037492737174 and training accuracy:0.996390223503
validation cost:0.0311532057822 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0341152623296 and training accuracy:0.996682941914
validation cost:0.02797492221 and validation accuracy:1.0
Training on :(4, 5)
Time taken:113.02063179
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.190335169435 and training accuracy:0.991702020168
validation cost:0.183990091085 and validation accuracy:0.991788327694
Training on :(6, 7)
training cost:0.0881213098764 and training accuracy:0.995580434799
validation cost:0.0849595293403 and validation accuracy:0.995437979698
Training on :(6, 7)
training cost:0.0598067119718 and training accuracy:0.997023522854
validation cost:0.0576120764017 and validation accuracy:0.996350347996
Training on :(6, 7)
training cost:0.0465094558895 and training accuracy:0.997564733028
validation cost:0.0447343327105 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0386684276164 and training accuracy:0.998015701771
validation cost:0.0371217094362 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0334331989288 and training accuracy:0.998376488686
validation cost:0.0320321284235 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0296543389559 and training accuracy:0.998556852341
validation cost:0.0283559840173 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0267777368426 and training accuracy:0.998647093773
validation cost:0.0255580898374 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0245016794652 and training accuracy:0.998917639256
validation cost:0.023345425725 and validation accuracy:1.0
Training on :(6, 7)
Time taken:121.324156046
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.257531195879 and training accuracy:0.957347750664
validation cost:0.258396476507 and validation accuracy:0.951977372169
Training on :(8, 9)
training cost:0.157806068659 and training accuracy:0.965915441513
validation cost:0.158970803022 and validation accuracy:0.95951038599
Training on :(8, 9)
training cost:0.122897341847 and training accuracy:0.970851182938
validation cost:0.124216862023 and validation accuracy:0.96798491478
Training on :(8, 9)
training cost:0.104078501463 and training accuracy:0.974669396877
validation cost:0.105322428048 and validation accuracy:0.976459503174
Training on :(8, 9)
training cost:0.0918255448341 and training accuracy:0.976904451847
validation cost:0.0928840860724 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.0829972401261 and training accuracy:0.979512035847
validation cost:0.0838367491961 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0762315317988 and training accuracy:0.980536401272
validation cost:0.0768524706364 and validation accuracy:0.98399245739
Training on :(8, 9)
training cost:0.0708254352212 and training accuracy:0.981840193272
validation cost:0.0712427124381 and validation accuracy:0.985875725746
Training on :(8, 9)
training cost:0.0663758143783 and training accuracy:0.983423352242
validation cost:0.0666075572371 and validation accuracy:0.985875725746
Training on :(8, 9)
Time taken:117.914283037
Method 3 test accuracy:0.813899993896
Training with lmbda:474313.824157, 2
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.223329275846 and training accuracy:0.997657477856
validation cost:0.217609897256 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0588664598763 and training accuracy:0.99809128046
validation cost:0.0582027807832 and validation accuracy:0.998244047165
Training on :(0, 1)
training cost:0.0329026244581 and training accuracy:0.998264789581
validation cost:0.0331324525177 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.023102754727 and training accuracy:0.998611807823
validation cost:0.0236389841884 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0179823227227 and training accuracy:0.998785376549
validation cost:0.0186521094292 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0148221068084 and training accuracy:0.998872101307
validation cost:0.0155552858487 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0126652261242 and training accuracy:0.99895888567
validation cost:0.01342903357 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.0110910469666 and training accuracy:0.99895888567
validation cost:0.0118674216792 and validation accuracy:0.997366130352
Training on :(0, 1)
training cost:0.00988608878106 and training accuracy:0.999132394791
validation cost:0.0106639899313 and validation accuracy:0.998244047165
Training on :(0, 1)
Time taken:126.870305061
Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
Length of test labels:2042
Train features:(11001, 3630)
Length of train labels:11001
Valid features:(1088, 3630)
Length of valid labels:1088
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(2, 3)
training cost:0.370019763708 and training accuracy:0.935914933681
validation cost:0.376309335232 and validation accuracy:0.936580896378
Training on :(2, 3)
training cost:0.184922486544 and training accuracy:0.958458304405
validation cost:0.190679311752 and validation accuracy:0.956801474094
Training on :(2, 3)
training cost:0.128788098693 and training accuracy:0.96918463707
validation cost:0.135282590985 and validation accuracy:0.966911792755
Training on :(2, 3)
training cost:0.101555794477 and training accuracy:0.974729597569
validation cost:0.108233600855 and validation accuracy:0.971507370472
Training on :(2, 3)
training cost:0.0851314216852 and training accuracy:0.978365600109
validation cost:0.0915655493736 and validation accuracy:0.972426474094
Training on :(2, 3)
training cost:0.0739758387208 and training accuracy:0.980456292629
validation cost:0.079976297915 and validation accuracy:0.975183844566
Training on :(2, 3)
training cost:0.0658098384738 and training accuracy:0.98327422142
validation cost:0.071308426559 and validation accuracy:0.979779422283
Training on :(2, 3)
training cost:0.0595215670764 and training accuracy:0.984819591045
validation cost:0.0645103156567 and validation accuracy:0.981617629528
Training on :(2, 3)
training cost:0.0544976219535 and training accuracy:0.986001253128
validation cost:0.0589988641441 and validation accuracy:0.982536792755
Training on :(2, 3)
Time taken:120.755630016
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:565018.665885, 9
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:615170.551021, 11
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:487065.64391, 46
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.814300000668
Training with lmbda:491840.424423, 47
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:565018.665885, 51
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:471675.378093, 57
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.812200009823
Training with lmbda:491840.424423, 61
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:505673.877019, 62
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.814999997616
Training with lmbda:584149.816945, 66
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.814999997616
Training with lmbda:615170.551021, 67
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:471675.378093, 71
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:474313.824157, 72
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.838999986649
Training with lmbda:474313.824157, 86
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:477341.317937, 87
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:534903.51815, 91
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.839299976826
Training with lmbda:558680.988358, 92
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
Time taken:120.982771873
Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.834299981594
Training with lmbda:618955.226464, 96
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Valid features:(1139, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Train features:(10250, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:120.446338177
Method 3 test accuracy:0.834399998188
Training with lmbda:628264.390862, 97
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Valid features:(1096, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.802500009537
Training with lmbda:477341.317937, 101
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:122.627251863
Method 3 test accuracy:0.802500009537
Training with lmbda:487065.64391, 102
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:558680.988358, 106
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:565018.665885, 107
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:628264.390862, 111
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Length of test labels:1983
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Valid features:(1062, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
Time taken:119.146580219
Method 3 test accuracy:0.804799973965
Training with lmbda:450943.771238, 112
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:487065.64391, 116
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:565018.665885, 121
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training with lmbda:615170.551021, 123
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Test features:(2042, 3630)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.834599971771
Training with lmbda:618955.226464, 124
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Valid features:(1013, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.77689999342
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Current mask:[1. 1. 1. 1. 0. 0. 0. 0. 0. 0.]
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Method 3 test accuracy:0.777000010014
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Current mask:[1. 1. 1. 1. 1. 1. 0. 0. 0. 0.]
Test features:(1874, 3630)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(4, 5)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(6, 7)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(8, 9)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(0, 1)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Training on :(2, 3)
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Test features:(1874, 3630)
Length of test labels:1874
Train features:(10250, 3630)
Length of train labels:10250
Valid features:(1013, 3630)
Length of valid labels:1013
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(4, 5)
training cost:0.274317592382 and training accuracy:0.978829264641
validation cost:0.278282016516 and validation accuracy:0.984205305576
Training on :(4, 5)
training cost:0.136532351375 and training accuracy:0.989170730114
validation cost:0.133826479316 and validation accuracy:0.994077026844
Training on :(4, 5)
training cost:0.0921739265323 and training accuracy:0.992975592613
validation cost:0.0872799903154 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0707256868482 and training accuracy:0.994243919849
validation cost:0.065092176199 and validation accuracy:0.99703848362
Training on :(4, 5)
training cost:0.0580754093826 and training accuracy:0.994731724262
validation cost:0.052214205265 and validation accuracy:0.998025655746
Training on :(4, 5)
training cost:0.0496971420944 and training accuracy:0.995219528675
validation cost:0.0438154153526 and validation accuracy:0.999012827873
Training on :(4, 5)
training cost:0.0437109954655 and training accuracy:0.996097564697
validation cost:0.0379007309675 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.039201028645 and training accuracy:0.996390223503
validation cost:0.0335043035448 and validation accuracy:1.0
Training on :(4, 5)
training cost:0.0356667041779 and training accuracy:0.996878027916
validation cost:0.0301006250083 and validation accuracy:1.0
Training on :(4, 5)
Time taken:115.706696033
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 0. 0.]
Test features:(1986, 3630)
Length of test labels:1986
Train features:(11087, 3630)
Length of train labels:11087
Valid features:(1096, 3630)
Length of valid labels:1096
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(6, 7)
training cost:0.193153351545 and training accuracy:0.992423534393
validation cost:0.185587748885 and validation accuracy:0.992700755596
Training on :(6, 7)
training cost:0.0928130075336 and training accuracy:0.995941221714
validation cost:0.0888188704848 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0638032630086 and training accuracy:0.997023522854
validation cost:0.0609439574182 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0499102883041 and training accuracy:0.997745096684
validation cost:0.047549277544 and validation accuracy:0.997262775898
Training on :(6, 7)
training cost:0.0416376367211 and training accuracy:0.998105883598
validation cost:0.0395478792489 and validation accuracy:0.9981752038
Training on :(6, 7)
training cost:0.0360835529864 and training accuracy:0.998556852341
validation cost:0.0341636016965 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0320620276034 and training accuracy:0.998556852341
validation cost:0.0302598532289 and validation accuracy:0.999087572098
Training on :(6, 7)
training cost:0.0289953015745 and training accuracy:0.9987372756
validation cost:0.0272812098265 and validation accuracy:1.0
Training on :(6, 7)
training cost:0.0265656970441 and training accuracy:0.998827457428
validation cost:0.0249212700874 and validation accuracy:1.0
Training on :(6, 7)
Time taken:126.945971966
Current mask:[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
Test features:(1983, 3630)
Length of test labels:1983
Train features:(10738, 3630)
Length of train labels:10738
Valid features:(1062, 3630)
Length of valid labels:1062
Repeat:0
training cost:2.30258536339 and training accuracy:0.0
validation cost:2.30258536339 and validation accuracy:0.0
Training on :(8, 9)
training cost:0.257991343737 and training accuracy:0.956975221634
validation cost:0.260393381119 and validation accuracy:0.951977372169
Training on :(8, 9)
training cost:0.160755380988 and training accuracy:0.965729176998
validation cost:0.163924396038 and validation accuracy:0.961393594742
Training on :(8, 9)
training cost:0.126498952508 and training accuracy:0.970571815968
validation cost:0.129837155342 and validation accuracy:0.968926548958
Training on :(8, 9)
training cost:0.107957966626 and training accuracy:0.973738133907
validation cost:0.11121352762 and validation accuracy:0.975517868996
Training on :(8, 9)
training cost:0.0958523452282 and training accuracy:0.975693821907
validation cost:0.0989248901606 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0871147885919 and training accuracy:0.977556347847
validation cost:0.0899727344513 and validation accuracy:0.97834277153
Training on :(8, 9)
training cost:0.0804052278399 and training accuracy:0.979325771332
validation cost:0.083045899868 and validation accuracy:0.980225980282
Training on :(8, 9)
training cost:0.0750273615122 and training accuracy:0.980722665787
validation cost:0.0774561986327 and validation accuracy:0.98116761446
Training on :(8, 9)
training cost:0.0705843567848 and training accuracy:0.982026457787
validation cost:0.0728142261505 and validation accuracy:0.98399245739
Training on :(8, 9)
Time taken:118.770991802
Method 3 test accuracy:0.775399982929
Total time:84619.5824039

Final accuracy

final_test_acc = pd.DataFrame({'Method3':method3_test_accs, 'lambdas':lmbdas})
final_test_acc.to_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_45_65-non_spk.csv')
final_test_acc

	Method3	lambdas
0	0.8134	450943.771238
1	0.8139	471675.378093
2	0.8138	474313.824157
3	0.8211	477341.317937
4	0.8215	487065.643910
5	0.8215	491840.424423
6	0.8217	505673.877019
7	0.8148	534903.518150
8	0.8153	558680.988358
9	0.8152	565018.665885
10	0.8156	584149.816945
11	0.8155	615170.551021
12	0.8155	618955.226464
13	0.8156	628264.390862
14	0.8001	450943.771238
15	0.8000	471675.378093
16	0.8001	474313.824157
17	0.8002	477341.317937
18	0.8003	487065.643910
19	0.8006	491840.424423
20	0.8003	505673.877019
21	0.8009	534903.518150
22	0.8008	558680.988358
23	0.8007	565018.665885
24	0.8006	584149.816945
25	0.7985	615170.551021
26	0.7986	618955.226464
27	0.7985	628264.390862
28	0.8335	450943.771238
29	0.8337	471675.378093
...	...	...
110	0.8050	618955.226464
111	0.8048	628264.390862
112	0.8333	450943.771238
113	0.8307	471675.378093
114	0.8307	474313.824157
115	0.8307	477341.317937
116	0.8307	487065.643910
117	0.8307	491840.424423
118	0.8311	505673.877019
119	0.8345	534903.518150
120	0.8346	558680.988358
121	0.8347	565018.665885
122	0.8348	584149.816945
123	0.8346	615170.551021
124	0.8346	618955.226464
125	0.8346	628264.390862
126	0.7776	450943.771238
127	0.7769	471675.378093
128	0.7770	474313.824157
129	0.7768	477341.317937
130	0.7771	487065.643910
131	0.7753	491840.424423
132	0.7754	505673.877019
133	0.7764	534903.518150
134	0.7765	558680.988358
135	0.7764	565018.665885
136	0.7764	584149.816945
137	0.7761	615170.551021
138	0.7761	618955.226464
139	0.7754	628264.390862

140 rows × 2 columns

Groupby $\lambda$s

acc_grouped_by_lmbda = final_test_acc.groupby('lambdas')
final_acc_grouped_by_lmbda = acc_grouped_by_lmbda.mean()
final_acc_grouped_by_lmbda.rename(columns={'Method3':'MEAN'}, inplace=True)
final_acc_grouped_by_lmbda['S.D'] = acc_grouped_by_lmbda.std()
final_acc_grouped_by_lmbda['MIN'] = acc_grouped_by_lmbda.min()
final_acc_grouped_by_lmbda['MAX'] = acc_grouped_by_lmbda.max()
final_acc_grouped_by_lmbda['MED'] = acc_grouped_by_lmbda.median()
final_acc_grouped_by_lmbda.reset_index(inplace=True)
display(final_acc_grouped_by_lmbda)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	450943.771238	0.81213	0.018777	0.7776	0.8387	0.80980
1	471675.378093	0.81269	0.018555	0.7769	0.8390	0.81290
2	474313.824157	0.81288	0.018448	0.7770	0.8390	0.81280
3	477341.317937	0.81355	0.018630	0.7768	0.8388	0.81320
4	487065.643910	0.81371	0.018603	0.7771	0.8390	0.81325
5	491840.424423	0.81358	0.018999	0.7753	0.8391	0.81335
6	505673.877019	0.81377	0.019057	0.7754	0.8388	0.81380
7	534903.518150	0.81384	0.019150	0.7764	0.8393	0.81410
8	558680.988358	0.81379	0.018741	0.7765	0.8362	0.81465
9	565018.665885	0.81382	0.018773	0.7764	0.8362	0.81480
10	584149.816945	0.81529	0.019207	0.7764	0.8362	0.81530
11	615170.551021	0.81528	0.019537	0.7761	0.8360	0.81525
12	618955.226464	0.81528	0.019550	0.7761	0.8360	0.81525
13	628264.390862	0.81491	0.019429	0.7754	0.8346	0.81525

Plots

mpl.rcParams['figure.figsize'] = 7,4.5
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.5
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 13
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 12

final_acc_grouped_by_lmbda.plot(y=['MEAN','MED','MAX'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Combine with previous $\lambda$s

prev_final_test_acc1 = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_75_10_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda1 = prev_final_test_acc1.groupby('lambdas')
prev_final_acc_grouped_by_lmbda1 = prev_acc_grouped_by_lmbda1.mean()
prev_final_acc_grouped_by_lmbda1.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda1['S.D'] = prev_acc_grouped_by_lmbda1.std()
prev_final_acc_grouped_by_lmbda1['MIN'] = prev_acc_grouped_by_lmbda1.min()
prev_final_acc_grouped_by_lmbda1['MAX'] = prev_acc_grouped_by_lmbda1.max()
prev_final_acc_grouped_by_lmbda1['MED'] = prev_acc_grouped_by_lmbda1.median()
prev_final_acc_grouped_by_lmbda1.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda1)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
2	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
3	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
4	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
5	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
6	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
7	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
8	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
9	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
10	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
11	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
12	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
13	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
14	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440

prev_final_test_acc2 = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_10_20_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda2 = prev_final_test_acc2.groupby('lambdas')
prev_final_acc_grouped_by_lmbda2 = prev_acc_grouped_by_lmbda2.mean()
prev_final_acc_grouped_by_lmbda2.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda2['S.D'] = prev_acc_grouped_by_lmbda2.std()
prev_final_acc_grouped_by_lmbda2['MIN'] = prev_acc_grouped_by_lmbda2.min()
prev_final_acc_grouped_by_lmbda2['MAX'] = prev_acc_grouped_by_lmbda2.max()
prev_final_acc_grouped_by_lmbda2['MED'] = prev_acc_grouped_by_lmbda2.median()
prev_final_acc_grouped_by_lmbda2.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda2)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	0.000000	0.71909	0.013358	0.6867	0.7346	0.72165
1	100471.885619	0.78694	0.020593	0.7600	0.8228	0.78455
2	110837.689046	0.78835	0.020678	0.7626	0.8240	0.78550
3	112156.912078	0.78858	0.020706	0.7631	0.8243	0.78575
4	113670.658968	0.78866	0.020647	0.7635	0.8243	0.78585
5	118532.821955	0.78888	0.021238	0.7638	0.8248	0.78630
6	120920.212212	0.78930	0.021262	0.7643	0.8249	0.78690
7	127836.938509	0.79036	0.021217	0.7647	0.8257	0.78750
8	142451.759075	0.79277	0.020593	0.7671	0.8270	0.78950
9	154340.494179	0.79669	0.018245	0.7692	0.8276	0.79450
10	157509.332943	0.79754	0.018844	0.7695	0.8276	0.79505
11	167074.908473	0.79855	0.018636	0.7704	0.8280	0.79605
12	182585.275511	0.79986	0.018529	0.7715	0.8288	0.79720
13	184477.613232	0.80001	0.018600	0.7717	0.8291	0.79740
14	189132.195431	0.80045	0.018781	0.7718	0.8296	0.79775

prev_final_test_acc3 = pd.read_csv('spike_sh_14lmbdas_ar1_3lyrs_he1_20_45_non_spk_classify.csv', 
                                  index_col=0)
prev_acc_grouped_by_lmbda3 = prev_final_test_acc3.groupby('lambdas')
prev_final_acc_grouped_by_lmbda3 = prev_acc_grouped_by_lmbda3.mean()
prev_final_acc_grouped_by_lmbda3.rename(columns={'Method3':'MEAN'}, inplace=True)
prev_final_acc_grouped_by_lmbda3['S.D'] = prev_acc_grouped_by_lmbda3.std()
prev_final_acc_grouped_by_lmbda3['MIN'] = prev_acc_grouped_by_lmbda3.min()
prev_final_acc_grouped_by_lmbda3['MAX'] = prev_acc_grouped_by_lmbda3.max()
prev_final_acc_grouped_by_lmbda3['MED'] = prev_acc_grouped_by_lmbda3.median()
prev_final_acc_grouped_by_lmbda3.reset_index(inplace=True)
display(prev_final_acc_grouped_by_lmbda3)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	201179.714048	0.80312	0.018350	0.7731	0.8303	0.79940
1	227094.222616	0.80550	0.018698	0.7757	0.8311	0.80060
2	230392.280196	0.80567	0.018672	0.7758	0.8311	0.80065
3	234176.647421	0.80583	0.018595	0.7759	0.8311	0.80085
4	246332.054888	0.80623	0.018735	0.7767	0.8315	0.80135
5	252300.530529	0.80687	0.019128	0.7769	0.8345	0.80195
6	269592.346273	0.80868	0.018645	0.7769	0.8352	0.80590
7	306129.397687	0.81075	0.019335	0.7781	0.8365	0.81640
8	335851.235448	0.81119	0.019834	0.7778	0.8352	0.81790
9	343773.332357	0.81128	0.019692	0.7781	0.8350	0.81765
10	367687.271182	0.81151	0.019817	0.7779	0.8360	0.81590
11	406463.188776	0.81217	0.019033	0.7779	0.8378	0.80835
12	411194.033080	0.81229	0.018940	0.7783	0.8378	0.80845
13	422830.488578	0.81246	0.019064	0.7779	0.8383	0.80875

df4 = final_acc_grouped_by_lmbda.copy(deep=True)
df4.drop([0], inplace=True)

df3 = prev_final_acc_grouped_by_lmbda3.copy(deep=True)
df3.drop([0], inplace=True)

df2 = prev_final_acc_grouped_by_lmbda2.copy(deep=True)
df2.drop([0], inplace=True)

df1 = prev_final_acc_grouped_by_lmbda1.copy(deep=True)
df1.drop([0], inplace=True)

final_df = pd.concat([df1, df2, df3, df4], axis=0)
final_df.reset_index(inplace=True, drop=True)
display(final_df)

	lambdas	MEAN	S.D	MIN	MAX	MED
0	75117.971405	0.78152	0.020727	0.7575	0.8158	0.77810
1	77709.422262	0.78250	0.020241	0.7608	0.8171	0.77825
2	78039.228020	0.78257	0.020269	0.7609	0.8173	0.77825
3	78417.664742	0.78260	0.020226	0.7611	0.8173	0.77825
4	79633.205489	0.78272	0.020203	0.7613	0.8177	0.77845
5	80230.053053	0.78300	0.020283	0.7614	0.8182	0.77885
6	81959.234627	0.78297	0.022364	0.7521	0.8185	0.77900
7	85612.939769	0.78450	0.021875	0.7530	0.8193	0.78235
8	88585.123545	0.78518	0.022124	0.7533	0.8197	0.78265
9	89377.333236	0.78485	0.021290	0.7540	0.8197	0.78310
10	91768.727118	0.78598	0.022291	0.7543	0.8201	0.78355
11	95646.318878	0.78604	0.020861	0.7586	0.8227	0.78410
12	96119.403308	0.78622	0.020912	0.7587	0.8229	0.78425
13	97283.048858	0.78645	0.020718	0.7590	0.8230	0.78440
14	100471.885619	0.78694	0.020593	0.7600	0.8228	0.78455
15	110837.689046	0.78835	0.020678	0.7626	0.8240	0.78550
16	112156.912078	0.78858	0.020706	0.7631	0.8243	0.78575
17	113670.658968	0.78866	0.020647	0.7635	0.8243	0.78585
18	118532.821955	0.78888	0.021238	0.7638	0.8248	0.78630
19	120920.212212	0.78930	0.021262	0.7643	0.8249	0.78690
20	127836.938509	0.79036	0.021217	0.7647	0.8257	0.78750
21	142451.759075	0.79277	0.020593	0.7671	0.8270	0.78950
22	154340.494179	0.79669	0.018245	0.7692	0.8276	0.79450
23	157509.332943	0.79754	0.018844	0.7695	0.8276	0.79505
24	167074.908473	0.79855	0.018636	0.7704	0.8280	0.79605
25	182585.275511	0.79986	0.018529	0.7715	0.8288	0.79720
26	184477.613232	0.80001	0.018600	0.7717	0.8291	0.79740
27	189132.195431	0.80045	0.018781	0.7718	0.8296	0.79775
28	227094.222616	0.80550	0.018698	0.7757	0.8311	0.80060
29	230392.280196	0.80567	0.018672	0.7758	0.8311	0.80065
30	234176.647421	0.80583	0.018595	0.7759	0.8311	0.80085
31	246332.054888	0.80623	0.018735	0.7767	0.8315	0.80135
32	252300.530529	0.80687	0.019128	0.7769	0.8345	0.80195
33	269592.346273	0.80868	0.018645	0.7769	0.8352	0.80590
34	306129.397687	0.81075	0.019335	0.7781	0.8365	0.81640
35	335851.235448	0.81119	0.019834	0.7778	0.8352	0.81790
36	343773.332357	0.81128	0.019692	0.7781	0.8350	0.81765
37	367687.271182	0.81151	0.019817	0.7779	0.8360	0.81590
38	406463.188776	0.81217	0.019033	0.7779	0.8378	0.80835
39	411194.033080	0.81229	0.018940	0.7783	0.8378	0.80845
40	422830.488578	0.81246	0.019064	0.7779	0.8383	0.80875
41	471675.378093	0.81269	0.018555	0.7769	0.8390	0.81290
42	474313.824157	0.81288	0.018448	0.7770	0.8390	0.81280
43	477341.317937	0.81355	0.018630	0.7768	0.8388	0.81320
44	487065.643910	0.81371	0.018603	0.7771	0.8390	0.81325
45	491840.424423	0.81358	0.018999	0.7753	0.8391	0.81335
46	505673.877019	0.81377	0.019057	0.7754	0.8388	0.81380
47	534903.518150	0.81384	0.019150	0.7764	0.8393	0.81410
48	558680.988358	0.81379	0.018741	0.7765	0.8362	0.81465
49	565018.665885	0.81382	0.018773	0.7764	0.8362	0.81480
50	584149.816945	0.81529	0.019207	0.7764	0.8362	0.81530
51	615170.551021	0.81528	0.019537	0.7761	0.8360	0.81525
52	618955.226464	0.81528	0.019550	0.7761	0.8360	0.81525
53	628264.390862	0.81491	0.019429	0.7754	0.8346	0.81525

Combined plots

mpl.rcParams['figure.figsize'] = 4.5,2.75
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.0
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 12
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 10
mpl.rcParams['font.size'] = 10

final_df.plot(y=['MEAN','MED','MAX', 'MIN'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('Accuracy')
plt.xlabel('$\lambda$')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

mpl.rcParams['figure.figsize'] = 4.5,2.75
mpl.rcParams['axes.labelsize'] = 12
mpl.rcParams['lines.linewidth'] = 1.0
mpl.rcParams['lines.markersize'] = 8
mpl.rcParams['xtick.labelsize'] = 12
mpl.rcParams['ytick.labelsize'] = 12
mpl.rcParams['legend.fontsize'] = 10
mpl.rcParams['font.size'] = 10

final_df.plot(y=['S.D'],x='lambdas')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ylabel('$\sigma$')
plt.xlabel('$\lambda$')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Some histograms

W_2

plt.hist(w_2.eval().flatten(), 100, log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(w_2.eval().flatten(), 100)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_W_2

plt.hist(new_big_omeg_w2.flatten(),bins=100,log=True)
#plt.yscale('log')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(new_big_omeg_w2.flatten(),bins=100,log=False)
#plt.yscale('log')
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_2

plt.hist(b_2.eval().flatten(), 100, log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(b_2.eval().flatten(), 100, log=False)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Omega_b_2

plt.hist(new_big_omeg_b2.flatten(),100,log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(new_big_omeg_b2.flatten(),100,log=False)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

W_3

plt.hist(w_3.eval().flatten(), 100, log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(w_3.eval().flatten(), 100, log=False)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

b_3

plt.hist(b_3.eval().flatten(), 10, log=True)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

plt.hist(b_3.eval().flatten(), 10, log=False)
plt.grid(b=True, which='both', color='w', linestyle='-', alpha=1.0)
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.show()

Init the writer with $\lambda$s (40.0, 65.0) non-spk classification (binary spike features)

path = '/home/ruthvik/Desktop/Summer 2017/tf_graph_outputs/mnist/continual_learning/original_mnist_5sets'
merged = tf.summary.merge_all()
train_writer = tf.summary.FileWriter(path + '/spike_sh_14lmbdas_ar1_3lyrs_he1_40_65_non_spk_classify_binary_feat', sess.graph)

Generate $\lambda$s

np.random.seed(100)
n_lmbdas = 15
a = np.random.uniform(low=40.0, high=65.0, size=(n_lmbdas,))
print(a)
print()
a = a*1.0e4
a = a[np.argsort(a)]
print(a)
print()
n_reps = 6
a = ([0]+a.tolist())*n_reps
n_lmbdas+=1
print(a, len(a))

[53.58512354 46.95923463 50.61293977 61.11940331 40.1179714  43.03922802
 56.76872712 60.64631888 43.41766474 54.37733324 62.28304886 45.23005305
 44.63320549 42.70942226 45.49243732]
()
[401179.71404774 427094.22261606 430392.28019578 434176.64742124
 446332.05488752 452300.5305293  454924.37315625 469592.34627345
 506129.39768728 535851.23544774 543773.33235681 567687.27118169
 606463.18877626 611194.03307998 622830.48857807]
()
([0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066, 0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066, 0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066, 0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066, 0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066, 0, 401179.7140477432, 427094.2226160638, 430392.2801957785, 434176.64742123825, 446332.05488751875, 452300.5305292974, 454924.37315624807, 469592.3462734491, 506129.3976872832, 535851.2354477413, 543773.3323568124, 567687.2711816947, 606463.1887762619, 611194.0330799759, 622830.488578066], 96)

Generate random weights

lmbdas = a
np.random.seed(0)
np_weights = []
low = -np.sqrt(2.0/(n_input)) # use 4 for sigmoid, 1 for tanh activation 
high = np.sqrt(2.0/(n_input))
for i in range(n_reps):
    np_weights.append(np.random.uniform(low=low,high=high,size=(n_input,n_middle)))

np_weights=[item for item in np_weights for i in range(n_lmbdas)]
print(len(np_weights), len(lmbdas))

(96, 96)

np.array_equal(np_weights[0], np_weights[15])

True

np.array_equal(np_weights[0], np_weights[16])

False

Commence training

START_TIME = time.time()
method3_test_accs = []
#INITIALIZE THE NETWORK
logging_count = 0
sess.run(init_op,options=run_options, run_metadata=run_metadata)
sess.graph.finalize()
for l in range(len(lmbdas)):
    print('Training with lmbda:{}, {}'.format(lmbdas[l], l))
    #sess.run(init_op,options=run_options, run_metadata=run_metadata)
    zeta = 1e-3
    new_big_omeg_w2 = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    new_big_omeg_b2 = np.zeros(shape=[1,n_middle], dtype=np.float32)
    w3_zeros = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    b3_zeros = np.zeros(shape=[1,n_out], dtype=np.float32)
    w3_accum = np.zeros(shape=[n_middle,n_out], dtype=np.float32)
    w3_accum = []
    b3_accum = np.zeros(shape=[1,n_out], dtype=np.float32)
    b3_accum = []
    reset_w2_grad_accum = np.zeros(shape=[n_input,n_middle], dtype=np.float32)
    reset_b2_grad_accum = np.zeros(shape=[1,n_middle], dtype=np.float32)

    start_w2 = None
    start_b2 = None
    sess.run(w_2_update_op, {w_2_update_placeholder:np_weights[l]})
    sess.run(b_2_update_op, {b_2_update_placeholder:np.zeros(shape=[1,n_middle],dtype=np.float32)})
    end_w2 = None
    end_b2 = None

    old_test_data = []
    historical_cross_test_acc = {}
    historical_train_accuracies = {}
    historical_train_costs = {}
    historical_val_accuracies = {}
    historical_val_costs = {}
    sets = [(0,1), (2,3), (4,5), (6,7), (8,9)]
    #sets = [(0,4),(5,9)]
    test_labels_set = []
    
    n_test_samples = []
    for a_set in range(len(sets)):
        current_set = sets[a_set]
        current_set_name = 'set'+str(a_set)
        mask_val = [0]*num_classes
        for i in range(0, current_set[1]+1):
            mask_val[i]=1
        set_mask_val = np.array(mask_val, dtype=np.float32)
        print('Current mask:{}'.format(set_mask_val))
        train_data_set, valid_data_set, test_data_set = extract_class_data(start=current_set[0],
                                                                      stop=current_set[1])
        train_images_set, train_labels_set = train_data_set[0], train_data_set[1]
        valid_images_set, valid_labels_set = valid_data_set[0], valid_data_set[1]
        test_images_set, test_labels_set = test_data_set[0], test_data_set[1]
        n_test_samples.append(len(test_labels_set))
        train_total = len(train_images_set)
        n_batches = len(train_images_set)/BATCH_SIZE
        #@@print('Number of batches:{}'.format(n_batches))


        #@@set_omegas = [tf.assign(big_omeg_w2, new_big_omeg_w2), tf.assign(big_omeg_b2, new_big_omeg_b2)]
        #@@sess.run(set_omegas)
        
        sess.run(big_omeg_w2_update_op, {big_omeg_w2_update_placeholder:new_big_omeg_w2})
        sess.run(big_omeg_b2_update_op, {big_omeg_b2_update_placeholder:new_big_omeg_b2})

        #@@reset_grad_accums = [tf.assign(w2_grad_accum, reset_w2_grad_accum),
        #@@                     tf.assign(b2_grad_accum, reset_b2_grad_accum)]
        #@@sess.run(reset_grad_accums)
        
        sess.run(w2_grad_accum_update_op, {w2_grad_accum_update_placeholder:reset_w2_grad_accum})
        sess.run(b2_grad_accum_update_op, {b2_grad_accum_update_placeholder:reset_b2_grad_accum})

        
        #@@reset_w3 = [tf.assign(w_3, w3_zeros), tf.assign(b_3, b3_zeros)]
        #@@sess.run(reset_w3)
        sess.run(w_3_update_op, {w_3_update_placeholder:w3_zeros})
        sess.run(b_3_update_op, {b_3_update_placeholder:b3_zeros})
    
        epochs = 10
        repeats = 1

        for repeat in range(repeats):
            #tf.set_random_seed(l)
            print('Repeat:{}'.format(repeat))
            train_accuracies = []
            train_costs = []
            val_accuracies = []
            val_costs = []
            best_val = 0
            first_params_set = None
            last_params_set = None
            T1 = time.time()
            for i in range(epochs):
                if(i==0):
                    start_w2, start_b2 = w_2.eval(), b_2.eval()
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: len(train_images_set)})
                #@@print('Epoch:{}'.format((i)))
                t1 = time.time()

                ### CALCULATE TRAIN COSTS AND TRAIN ACCURACIES
                train_cost, train_accuracy = sess.run([cost, acct_res] ,feed_dict = {drop_out : 0.0, 
                                                                                     set1_mask:set_mask_val})
                train_costs.append(train_cost)
                train_accuracies.append(train_accuracy)
                #train_writer.add_summary(summary,logging_count)

                print('training cost:{} and training accuracy:{}'.format(train_costs[i], train_accuracies[i]))

                ### CALCULATE VALID COSTS AND VALID ACCURACIES
                sess.run(iter.initializer, feed_dict={a_1: valid_images_set, y: valid_labels_set,
                                                      batch_size: len(valid_images_set)})
                _, _, val_acc, val_cost, _ = sess.run([predictions,acct_mat,acct_res, cost, a_3],
                                                      feed_dict = {drop_out : 0.0,set1_mask:set_mask_val})
                val_costs.append(val_cost)
                val_accuracies.append(val_acc)

                if(val_acc>best_val):
                    best_val = val_acc
                    best_params_set1 = [(w_2.eval(),b_2.eval()),(w_3.eval(),b_3.eval())]
                print('validation cost:{} and validation accuracy:{}'.format(val_cost, val_acc))   
                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                      batch_size: BATCH_SIZE})


                sess.run(iter.initializer, feed_dict={a_1: train_images_set, y: train_labels_set,
                                                  batch_size: BATCH_SIZE})
                print('Training on :{}'.format(current_set))
                for j in range(n_batches):

                    if(not (np.isnan(w_2.eval().any() and np.isnan(w_3.eval()).any()))):
                        #if(a_set==1):
                        #    print(j, w_2.eval().sum(), w_3.eval().sum())
                        if(((j)% 1000 ==0)):
                            logging_count+=1
                            summary,_,_ = sess.run([merged,step, omega_step], 
                                                 feed_dict = {drop_out:0.0,batch_size: BATCH_SIZE,tau:0.5,
                                                              set1_mask:set_mask_val,eta:0.001,
                                                              lmbda:lmbdas[l],n_tot:train_total})
                            #train_writer.add_summary(summary, (i+1)*j)
                            train_writer.add_summary(summary, logging_count)
                        else:
                            sess.run([step, omega_step],feed_dict = {drop_out:0.0,batch_size:BATCH_SIZE,
                                                                     tau:0.5,set1_mask:set_mask_val,
                                                                     eta:0.001,lmbda:lmbdas[l],
                                                                     n_tot:train_total})
                    else:
                        print('Nan encountered in epoch:{} and batch:{}'.format(i, j))
                #@@print('Epoch time:{}'.format(time.time()-t1))


            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,final_test_acc,_ = sess.run([predictions, acct_res, a_3], 
                                                                  feed_dict = {drop_out:0.0, 
                                                                               set1_mask:set_mask_val})
            #@@print('Final test accuracy is:{}'.format(final_test_acc))
            end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
            #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
            #@@sess.run(update_star_wbs)
            sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
            sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
            
            
            #all_final_test_accs_set1.append(final_test_acc)


            #@@best_step = [tf.assign(w_2,best_params_set1[0][0]), tf.assign(b_2,best_params_set1[0][1]),
            #@@             tf.assign(w_3,best_params_set1[1][0]),tf.assign(b_3,best_params_set1[1][1])]
            #@@sess.run(best_step)
            
            sess.run(w_2_update_op, {w_2_update_placeholder:best_params_set1[0][0]})
            sess.run(b_2_update_op, {b_2_update_placeholder:best_params_set1[0][1]})
            
            sess.run(w_3_update_op, {w_3_update_placeholder:best_params_set1[1][0]})
            sess.run(b_3_update_op, {b_3_update_placeholder:best_params_set1[1][1]})
            
            sess.run(iter.initializer, feed_dict={a_1: test_images_set, y: test_labels_set,
                                                      batch_size: len(test_images_set)})
            _,test_acc_corresp_best_val,_ = sess.run([predictions, acct_res, a_3],
                                                     feed_dict = {drop_out:0.0,set1_mask:set_mask_val})

            #@@print('Test accuracy corresp to best val acc:{}'.format(test_acc_corresp_best_val))
            print('Time taken:{}'.format(time.time()-T1))
            #w3_list.append(w_3.eval())
            w3_accum.append(w_3.eval())
            #b3_list.append(b_3.eval())
            b3_accum.append(b_3.eval())
            if(i==epochs-1):
                if(test_acc_corresp_best_val>final_test_acc):
                    end_w2, end_b2, end_w3, end_b3 = w_2.eval(), b_2.eval(), w_3.eval(), b_3.eval()
                    #all_final_test_accs_set1[-1] = test_acc_corresp_best_val
                    #@@update_star_wbs = [tf.assign(star_w2,end_w2),tf.assign(star_b2,end_b2)]
                    #@@sess.run(update_star_wbs)
                    
                    sess.run(star_w2_update_op, {star_w2_update_placeholder:end_w2})
                    sess.run(star_b2_update_op, {star_b2_update_placeholder:end_b2})
                    

                #@@best_step = [tf.assign(w_2,end_w2), tf.assign(b_2,end_b2),
                #@@         tf.assign(w_3,end_w3),tf.assign(b_3,end_b3)]
                #@@sess.run(best_step)
                
                
                sess.run(w_2_update_op, {w_2_update_placeholder:end_w2})
                sess.run(b_2_update_op, {b_2_update_placeholder:end_b2})
                
                sess.run(w_3_update_op, {w_3_update_placeholder:end_w3})
                sess.run(b_3_update_op, {b_3_update_placeholder:end_b3})

                first_params_set = [(start_w2, start_b2)]
                last_params_set = [(end_w2, end_b2)]

                small_omegas = [(w2_grad_accum.eval(),b2_grad_accum.eval())]

                delta_ws = map(lambda x,y: np.square(x-y)+zeta,[item[0] for item in last_params_set],
                           [item[0] for item in first_params_set])

                delta_bs = map(lambda x,y: np.square(x-y)+zeta,[item[1] for item in last_params_set],
                           [item[1] for item in first_params_set])
                delta_wbs = zip(delta_ws, delta_bs)

                big_omegas_ws = map(lambda x,y: (x/y),[item[0] for item in small_omegas],
                           [item[0] for item in delta_wbs])            
                big_omegas_bs = map(lambda x,y: (x/y),[item[1] for item in small_omegas],
                           [item[1] for item in delta_wbs])

                big_omegas = zip(big_omegas_ws, big_omegas_bs)
                new_big_omeg_w2 += big_omegas[0][0]
                new_big_omeg_b2 += big_omegas[0][1]
                #@@print('omegW2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_w2.max(),
                #@@                                                new_big_omeg_w2.mean(),
                #@@                                                new_big_omeg_w2.std()))
                #@@print('omegb2-MAXIMUM:{},MEAN:{},STD:{}'.format(new_big_omeg_b2.max(),
                #@@                                                new_big_omeg_b2.mean(),
                #@@                                                new_big_omeg_b2.std()))

        historical_train_accuracies[current_set_name]=train_accuracies
        historical_train_costs[current_set_name]=train_costs
        historical_val_accuracies[current_set_name]=val_accuracies
        historical_val_costs[current_set_name]=val_costs
    
    #######Method 3 ###########
    w3_set_rows = []
    offset=0
    for item in w3_accum:
        w3_set_rows.append(item[:,offset:offset+2])
        offset+=2


    w3_set_row_avgs = [item.mean() for item in w3_set_rows]
    final_w3 = map(lambda x,y:x-y,w3_set_rows, w3_set_row_avgs)
    final_w3 = np.concatenate(final_w3, axis=1)

    b3_set_rows = []
    offset=0
    for item in b3_accum:
        b3_set_rows.append(item[:,offset:offset+2])
        offset+=2
    b3_set_row_avgs = [item.mean() for item in b3_set_rows]
    final_b3 = map(lambda x,y:x-y,b3_set_rows, b3_set_row_avgs)
    final_b3 = np.concatenate(final_b3, axis=1)

    #@@set_w3 = [tf.assign(w_3, final_w3), tf.assign(b_3, final_b3)]
    #@@sess.run(set_w3)
    sess.run(w_3_update_op, {w_3_update_placeholder:final_w3})
    sess.run(b_3_update_op, {b_3_update_placeholder:final_b3})

    sess.run(iter.initializer, feed_dict={a_1: test_images, y: to_categorical(test_labels,num_classes=num_classes),
                                                      batch_size: len(test_images)})
    _,final_test_acc,_ = sess.run([predictions, acct_res, a_3],
                                  feed_dict = {drop_out:0.0,set1_mask:set_mask_val})
    method3_test_accs.append(final_test_acc)
    print('Method 3 test accuracy:{}'.format(final_test_acc))
    
    
train_writer.close()
print('Total time:{}'.format(time.time()-START_TIME))

Training with lmbda:0, 0
Current mask:[1. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
Test features:(2115, 3630)
Length of test labels:2115
Train features:(11526, 3630)
Length of train labels:11526
Valid features:(1139, 3630)
Length of valid labels:1139
Repeat:0
training cost:2.30258536339 and training accuracy:0.467811912298
validation cost:2.30258536339 and validation accuracy:0.473222136497
Training on :(0, 1)
training cost:0.440640777349 and training accuracy:0.977095246315
validation cost:0.432918131351 and validation accuracy:0.969271302223
Training on :(0, 1)